数据库培训

数据库培训

数据库培训,Database培训

Testi...Client Testimonials

SQL Programming

Great teacher with in depth knowledge and real life, relevant examples. Engaging and always ensures a section is understood before moving on to next.

 

Sade Okiji

SQL Programming

Good

 

Zan Sue - Net Media Planet

SQL Programming

The course content was adapted well to suit my current knowledge and capabilities. Specific topics I requested were covered well.

 

Steven Sirman - Corus Group

SQL Programming

The trainer is a great trainer and has very professional tone. I would definitely like to attend a SQL Advanced course in the near future which is hosted by the same trainer.

 

Mitul. P. Parmar - Cancer Research UK

SQL Programming

Having a 1-1 training course was very effective, it meant I was less intimidated as I could stop the trainer to ask questions where I may otherwise have been reluctant to ask. The trainer was very good at explaining everything that I needed to know and took the time to make sure going back where needed to re explain when I got stuck.The training was very clear and concise and tailored very well to my own individual needs.The training has covered all the points it needed too. — Robert Craft

 

Zurich Employment Services Limited

SQL Programming

This course was truly fantastic, spot-on! It covers the basics but also details of SQL language. I will definitely recommended this course to my colleagues. There simply isn't another course out there that would give you so much in such a short period of time, great value for money. A must for any beginner or intermediate SQL user!

 

Piotr Olczak Planing Officer - Brunel University

SQL Programming

I really can't praise this course and the trainers highly enough! They were both extremely well qualified and made the subject interesting. The pace of the course was excellent and I've come away feeling very satisfied with the skills I've learned.

 

Susan Elder - Merrill Lynch

SQL Fundamentals

The trainer was extremely knowledgeable and ensured that I properly understand at every steps. I am very happy with the course.

 

Takuya Yorita - Mizuho Corporate Bank Ltd

SQL Fundamentals

Shafeeq has good knowledge of SQL and was keen to share this.

Ben Cook - Quest Software

SQL Fundamentals

Nice atmosphere, worked examples, lots of info to take away.

Simon Lingard - Avon Somerset & Wiltshire Cancer Services (ASWCS)

SQL Fundamentals

The trainer was very good and modified the course to meet the knowledge I already had.

I liked it was 1 to 1

Charlotte Rundle - Knapp Systemintegration GmbH

MongoDB for Administrators

monitoring

Ling Xiao - The Globe and Mail

MongoDB for Administrators

Good content and excercises

Richard Smallwood - PayPoint Network Limited

MongoDB for Developers

open mind and communication

Oleksiy Deliyev - Insight Enterprises

Oracle SQL Intermediate

Trainer provided some topic and support it with plenty of exercises. We had a chance to apply knowledge by doing them on our own.

- UBS Business Solutions Poland Sp. z o.o.

Oracle SQL Intermediate

Access to trainers individual support in resolving exercises.

Tomasz Czornak - UBS Business Solutions Poland Sp. z o.o.

Fundamentals of Cassandra DB

- Trainer had good practical knowledge about using cassandra day-to-day at least for development purposes
- Catering (snacks, coffee hour) were great
- 3 days length was good

Mika Linnanoja - Rovio

MongoDB for Developers

super athmosphere, working with mongo shell

Jan Sturm - AVL List GmbH

MariaDB Database Administration

Training material was very informative. Learned a lot

Yaw Asamoah - FEDERAL AVIATION ADMINISTRATION

MariaDB Database Administration

lessons and examples

Kelly Taylor - FEDERAL AVIATION ADMINISTRATION

MariaDB Database Administration

he adapted to the experience of the group - gave us great value for a beginners course.

Rich Mickey - FEDERAL AVIATION ADMINISTRATION

MongoDB for Administrators

The structure and pace of the class was great.

David Lacy - Availity

MongoDB for Administrators

The depth of the Mongo db training was explored from basic to advanced, I felt it was a little too much to squeeze into 2 days but I did get exposure to all aspects of Mongo db.

Bay Sayarath - Availity

MongoDB for Administrators

Relevant to need.

Damon Grube - Availity

MongoDB for Administrators

Most of the hands on stuff was good.

Andrew Bauer - Availity

MongoDB for Administrators

I had attended a different training given by the mongo team. I like this one a lot better in terms of simplicity and course material. Thanks for helping us out.

Patience, clear and to the point.

V. Rai - New Jersey

MongoDB for Developers

He (the trainer) used good real world examples and pitched the exercises at the right level

Martin Davies- Capgemini UK Plc

Developing Desktop Applications with Visual Studio 2012, VB.NET and SQL Server 2012

I appreciated Fulvio's wide breadth of knowledge. Not only was he familiar with the course content, but he also knew of constructs in languages we were familiar with to make examples more meaningful to us. During intervals he shared his knowledge of technologies and solutions outside the training scope to provide insights into other solutions we could use in future (and future training).

Raphael Keymer - Markit Valuations Limited

MariaDB Database Administration

Enjoyed the pace, delivery and technical knowhow of the trainer

Junaid Kalang - Capita CSL

PostgreSQL Administration and Development

Very in depth knowledge on the subject matter. No "I'll have to look into that and get back to you, just knew it all"

David Marshall - TIO Networks CORP

SQL Fundamentals

The trainer, he was knowledgeable, engaging, and easy to learn from. he encouraged a lot of hands on learning

Shawn McAndrew - Halifax Regional Municipality

SQL Fundamentals

I learned a LOOOOOT

Kamil Szmid - UBS Business Solutions Poland Sp. z o. o.

Cassandra for Developers

Topics approached. Very complete.

Carlos Eloi Barros - Farfetch Portugal - Unipessoal, Lda

Cassandra for Developers

The last exercise was very good.

José Monteiro - Farfetch Portugal - Unipessoal, Lda

Cassandra for Developers

I already using and have a application in production with cassandra so mostly of the topics i already know but the data modeling and advanced topics are a lot interesting.

Tiago Costa - Farfetch Portugal - Unipessoal, Lda

Cassandra for Developers

There was a lot of knowledge and material shared that will help me to do my current tasks.

Miguel Fernandes - Farfetch Portugal - Unipessoal, Lda

Cassandra for Developers

The amount of exercises. We could immediately apply the knowledge shared and ensure the information was on point.

Joana Pereira - Farfetch Portugal - Unipessoal, Lda

Cassandra for Developers

All technical explanation and theoretical introduction

André Santos - Farfetch Portugal - Unipessoal, Lda

Cassandra for Developers

Very good explanations with in depth examples

Rui Magalhaes - Farfetch Portugal - Unipessoal, Lda

Cassandra for Developers

The practical exercises and examples of implementing examples of real models and contexts

Leandro Gomes - Farfetch Portugal - Unipessoal, Lda

Building Web Apps using the MEAN stack

The labs were interesting and probably the most useful learning tool to me. Anything I missed or forgot about was relearned or reinforced in the labs.

Joseph Fuerst - The Aerospace Corporation

MongoDB for Administrators

tailored to cover our organisations questions.

Robin Bell - Egress Software Technologies

MongoDB for Administrators

The clear depth of knowledge the trainer had, which really shone when combined with his evident enthusiasm for the subject.

Joseph Brailsford - Egress Software Technologies

MongoDB for Administrators

Even though I have been using MongoDB for a while, there were still some new "basic" things that Kamil taught us - as well as teaching us the advanced topics we need to move our projects forwards.

Adam McKay - Egress Software Technologies

A practical introduction to Data Analysis and Big Data

Willingness to share more

Balaram Chandra Paul - MOL Information Technology Asia Limited

Data Analysis with Hive/HiveQL

Liked very much the interactive way of learning.

Luigi Loiacono - Proximus

Data Analysis with Hive/HiveQL

It was a very practical training, I liked the hands-on exercises.

Proximus

其他课程类别

数据库大纲

代码 名字 期限 概览
pgsqladm PostgreSQL Administration and Development 28小时 This course handles the administration and performance tuning of PostgreSQL databases. Attendees will learn the use of specialised PostgreSQL (AKA Postgres) modules such as replication, connection pooling and full text searching. What is PostgreSQL? A Brief History of PostgreSQL Conventions Further Information Bug Reporting Guidelines Introduction to PostgreSQL Installation and Creating Database The SQL Language Advanced Features The SQL Language SQL Syntax Data Definition Data Manipulation Queries Data Types Functions and Operators Type Conversion Indexes Full Text Search Concurrency Control Performance Tips Server Administration Installation from Source Code Installation from Source Code on Windows Server Setup and Operation Server Configuration Client Authentication Database Roles Managing Databases Localization Routine Database Maintenance Tasks Backup and Restore High Availability, Load Balancing, and Replication Recovery Configuration Monitoring Database Activity Monitoring Disk Usage Reliability and the Write-Ahead Log Regression Tests Client Interfaces libpq - C Library Large Objects ECPG - Embedded SQL in C The Information Schema Server Programming Extending SQL Triggers The Rule System Procedural Languages PL/pgSQL - SQL Procedural Language PL/Tcl - Tcl Procedural Language PL/Perl - Perl Procedural Language PL/Python - Python Procedural Language Server Programming Interface Internals Overview of PostgreSQL Internals System Catalogs Frontend/Backend Protocol PostgreSQL Coding Conventions Native Language Support Writing A Procedural Language Handler Writing A Foreign Data Wrapper Genetic Query Optimizer Index Access Method Interface Definition GiST Indexes GIN Indexes Database Physical Storage BKI Backend Interface How the Planner Uses Statistics
bigdatastore Big Data Storage Solution - NoSQL 14小时 When traditional storage technologies don't handle the amount of data you need to store there are hundereds of alternatives. This course try to guide the participants what are alternatives for storing and analyzing Big Data and what are theirs pros and cons. This course is mostly focused on discussion and presentation of solutions, though hands-on exercises are available on demand. Limits of Traditional Technologies SQL databases Redundancy: replicas and clusters Constraints Speed Overview of database types Object Databases Document Store Cloud Databases Wide Column Store Multidimensional Databases Multivalue Databases Streaming and Time Series Databases Multimodel Databases Graph Databases Key Value XML Databases Distribute file systems Popular NoSQL Databases MongoDB Cassandra Apache Hadoop Apache Spark other solutions NewSQL Overview of available solutions Performance Inconsitencies Document Storage/Search Optimized Solr/Lucene/Elasticsearch other solutions
kdd Knowledge Discover in Databases (KDD) 21小时 Knowledge discovery in databases (KDD) is the process of discovering useful knowledge from a collection of data. Real-life applications for this data mining technique include marketing, fraud detection, telecommunication and manufacturing. In this course, we introduce the processes involved in KDD and carry out a series of exercises to practice the implementation of those processes. Audience     Data analysts or anyone interested in learning how to interpret data to solve problems Format of the course     After a theoretical discussion of KDD, the instructor will present real-life cases which call for the application of KDD to solve a problem. Participants will prepare, select and cleanse sample data sets and use their prior knowledge about the data to propose solutions based on the results of their observations. Introduction     KDD vs data mining Establishing the application domain Establishing relevant prior knowledge Understanding the goal of the investigation Creating a target data set Data cleaning and preprocessing Data reduction and projection Choosing the data mining task Choosing the data mining algorithms Interpreting the mined patterns
matlabdsandreporting MATLAB Fundamentals, Data Science & Report Generation 126小时 In the first part of this training, we cover the fundamentals of MATLAB and its function as both a language and a platform.  Included in this discussion is an introduction to MATLAB syntax, arrays and matrices, data visualization, script development, and object-oriented principles. In the second part, we demonstrate how to use MATLAB for data mining, machine learning and predictive analytics. To provide participants with a clear and practical perspective of MATLAB's approach and power, we draw comparisons between using MATLAB and using other tools such as spreadsheets, C, C++, and Visual Basic. In the third part of the training, participants learn how to streamline their work by automating their data processing and report generation. Throughout the course, participants will put into practice the ideas learned through hands-on exercises in a lab environment. By the end of the training, participants will have a thorough grasp of MATLAB' capabilities and will be able to employ it for solving real-world data science problems as well as for streamlining their work through automation. Assessments will be conducted throughout the course to guage progress. Format of the course Course includes theoretical and practical exercises, including case discussions, sample code inspection, and hands-on implementation. Note Practice sessions will based on pre-arranged sample data report templates. If you have specific requirements, please contact us to arrange Introduction MATLAB for data science and reporting   Part 01: MATLAB fundamentals Overview     MATLAB for data analysis, visualization, modeling, and programming. Working with the MATLAB user interface Overview of MATLAB syntax Entering commands     Using the command line interface Creating variables     Numeric vs character data Analyzing vectors and matrices     Creating and manipulating     Performing calculations Visualizing vector and matrix data Working with data files     Importing data from Excel spreadsheets Working with data types     Working with table data Automating commands with scripts     Creating and running scripts     Organizing and publishing your scripts Writing programs with branching and loops     User interaction and flow control Writing functions     Creating and calling functions     Debugging with MATLAB Editor Applying object-oriented programming principles to your programs   Part 02: MATLAB for data science Overview     MATLAB for data mining, machine learning and predictive analytics Accessing data     Obtaining data from files, spreadsheets, and databases     Obtaining data from test equipment and hardware     Obtaining data from software and the Web Exploring data     Identifying trends, testing hypotheses, and estimating uncertainty Creating customized algorithms Creating visualizations Creating models Publishing customized reports Sharing analysis tools     As MATLAB code     As standalone desktop or Web applications Using the Statistics and Machine Learning Toolbox Using the Neural Network Toolbox   Part 03: Report generation Overview     Presenting results from MATLAB programs, applications, and sample data     Generating Microsoft Word, PowerPoint®, PDF, and HTML reports.     Templated reports     Tailor-made reports         Using organization’s templates and standards Creating reports interactively vs programmatically     Using the Report Explorer     Using the DOM (Document Object Model) API Creating reports interactively using Report Explorer     Report Explorer Examples         Magic Squares Report Explorer Example     Creating reports         Using Report Explorer to create report setup file, define report structure and content     Formatting reports         Specifying default report style and format for Report Explorer reports     Generating reports         Configuring Report Explorer for processing and running report     Managing report conversion templates         Copying and managing Microsoft Word , PDF, and HTML conversion templates for Report Explorer reports     Customizing Report Conversion templates         Customizing the style and format of Microsoft Word and HTML conversion templates for Report Explorer reports     Customizing components and style sheets         Customizing report components, define layout style sheets Creating reports programmatically in MATLAB     Template-Based Report Object (DOM) API Examples         Functional report         Object-oriented report         Programmatic report formatting     Creating report content         Using the Document Object Model (DOM) API     Report format basics         Specifying format for report content     Creating form-based reports         Using the DOM API to fill in the blanks in a report form     Creating object-oriented reports         Deriving classes to simplify report creation and maintenance     Creating and formatting report objects         Lists, tables, and images     Creating DOM Reports from HTML         Appending HTML string or file to a Microsoft® Word, PDF, or HTML report generated by Document Object Model (DOM) API     Creating report templates         Creating templates to use with programmatic reports     Formatting page layouts         Formatting pages in Microsoft Word and PDF reports Summary and closing remarks
416 Introduction to Firebird 14小时 Classic, SuperClassic or Superserver? Installation packages Embedded Server for Windows What is in the kit? Default disk locations Linux Windows Installing Firebird Installing the Firebird server Installing multiple servers Testing your installation Performing a client-only install Server configuration and management User management: gsec Security Windows Control Panel applets Administration tools Working with databases Connection strings Connecting to an existing database Creating a database using isql Firebird SQL Protecting your data Backup How to corrupt a database
cassdev Cassandra for Developers 21小时 This course will introduce Cassandra –  a popular NoSQL database.  It will cover Cassandra principles, architecture and data model.   Students will learn data modeling  in CQL (Cassandra Query Language) in hands-on, interactive labs.  This session also discusses Cassandra internals and some admin topics. Duration : 3 days Audience : Developers Section 1: Introduction to Big Data / NoSQL NoSQL overview CAP theorem When is NoSQL appropriate Columnar storage NoSQL ecosystem Section 2 : Cassandra Basics Design and architecture Cassandra nodes, clusters, datacenters Keyspaces, tables, rows and columns Partitioning, replication, tokens Quorum and consistency levels Labs : interacting with cassandra using CQLSH Section 3: Data Modeling – part 1 introduction to CQL CQL Datatypes creating keyspaces & tables Choosing columns and types Choosing primary keys Data layout for rows and columns Time to live (TTL) Querying with CQL CQL updates Collections (list / map / set) Labs : various data modeling exercises using CQL ; experimenting with queries and supported data types Section 4: Data Modeling – part 2 Creating and using secondary indexes composite keys (partition keys and clustering keys) Time series data Best practices for time series data Counters Lightweight transactions (LWT) Labs : creating and using indexes;  modeling time series data Section 5 : Data Modeling Labs  : Group design session multiple use cases from various domains are presented students work in groups to come up designs and models discuss various designs, analyze decisions Lab : implement one of the scenario Section 6: Cassandra drivers Introduction to Java driver CRUD (Create / Read / Update, Delete) operations using Java client Asynchronous queries Labs : using Java API for Cassandra Section 7 : Cassandra Internals understand Cassandra design under the hood sstables, memtables, commit log read path / write path caching vnodes Section 8: Administration Hardware selection Cassandra distributions Cassandra best practices (compaction, garbage collection,) troubleshooting tools and tips Lab : students install Cassandra, run benchmarks Section 9:  Bonus Lab (time permitting) Implement a music service like Pandora / Spotify on Cassandra
scylladb Scylla database 21小时 Scylla is an open-source distributed NoSQL data store. It is compatible with Apache Cassandra but performs at significantly higher throughputs and lower latencies. In this course, participants will learn about Scylla's features and architecture while obtaining practical experience with setting up, administering, monitoring, and troubleshooting Scylla.   Audience     Database administrators     Developers     System Engineers Format of the course     The course is interactive and includes discussions of the principles and approaches for deploying and managing Scylla distributed databases and clusters. The course includes a heavy component of hands-on exercises and practice. Introduction to Scylla Installing and running Scylla Understanding distributed databases Scylla's data model and architecture Working with CQL (Cassandra Query Language) Setting up a Scylla cluster Scylla tools Database administration Troubleshooting Scylla
TalendDI Talend Open Studio for Data Integration 28小时 Talend Open Studio for Data Integration is an open-source data integration product used to combine, convert and update data in various locations across a business. In this instructor-led, live training, participants will learn how to use the Talend ETL tool to carry out data transformation, data extraction, and connectivity with Hadoop, Hive, and Pig.   By the end of this training, participants will be able to Explain the concepts behind ETL (Extract, Transform, Load) and propagation Define ETL methods and ETL tools to connect with Hadoop Efficiently amass, retrieve, digest, consume, transform and shape big data in accordance to business requirements Audience Business intelligence professionals Project managers Database professionals SQL Developers ETL Developers Solution architects Data architects Data warehousing professionals System administrators and integrators Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.  
gfsjeeint Administering GlassFish Server with Java EE applications introduction 21小时 Introduction to GlassFish Server Overview of the Java EE Architecture GlassFish Background GlassFish Basic Architecture GlassFish Basic Features Installing and upgrading Installation Upgrade Administering and deploying applications Administration High Availability Administration Security Application Deployment Message Queue Administration Troubleshooting Troubleshooting Error Message Scaling and tuning the performance Deployment Planning Performance Tuning Developing applications Your First Cup: An Introduction to the Java EE Platform The Java EE Tutorial Application Development Guide Message Queue Developer's Guide for Java Clients Message Queue Developer's Guide for JMX Clients Message Queue Developer's Guide for C Clients Extending and embedding Add-On Component Development Guide Embedded Server Guide
hbasedev HBase for Developers 21小时 This course introduces HBase – a NoSQL store on top of Hadoop.  The course is intended for developers who will be using HBase to develop applications,  and administrators who will manage HBase clusters. We will walk a developer through HBase architecture and data modelling and application development on HBase. It will also discuss using MapReduce with HBase, and some administration topics, related to performance optimization. The course  is very  hands-on with lots of lab exercises. Duration : 3 days Audience : Developers  & Administrators Section 1: Introduction to Big Data & NoSQL Big Data ecosystem NoSQL overview CAP theorem When is NoSQL appropriate Columnar storage HBase and NoSQL Section 2 : HBase Intro Concepts and Design Architecture (HMaster and Region Server) Data integrity HBase ecosystem Lab : Exploring HBase Section 3 : HBase Data model Namespaces, Tables and Regions Rows, columns, column families, versions HBase Shell and Admin commands Lab : HBase Shell Section 3 : Accessing HBase using Java API Introduction to Java API Read / Write path Time Series data Scans Map Reduce Filters Counters Co-processors Labs (multiple) : Using HBase Java API to implement  time series , Map Reduce, Filters and counters. Section 4 : HBase schema Design : Group session students are presented with real world use cases students work in groups to come up with design solutions discuss / critique and learn from multiple designs Labs : implement a scenario in HBase Section 5 : HBase Internals Understanding HBase under the hood Memfile / HFile / WAL HDFS storage Compactions Splits Bloom Filters Caches Diagnostics Section 6 : HBase installation and configuration hardware selection install methods common configurations Lab : installing HBase Section 7 : HBase eco-system developing applications using HBase interacting with other Hadoop stack (MapReduce, Pig, Hive) frameworks around HBase advanced concepts (co-processors) Labs : writing HBase applications Section 8 : Monitoring And Best Practices monitoring tools and practices optimizing HBase HBase in the cloud real world use cases of HBase Labs : checking HBase vitals
berkeleydb Berkeley DB for developers 21小时 Berkeley DB (BDB) is a software library intended to provide a high-performance embedded database for key/value data. Berkeley DB is written in C with API bindings for C++, C#, Java, Perl, PHP, Python, Ruby, Smalltalk, Tcl, and many other programming languages. Berkeley DB is not a relational database.[1] This course will introduce the architecture and capabilities of Berkeley DB and walk participants through the development of their own sample application using Berkeley DB. Audience     Application developers     Software engineers     Technical consultants Format of the course     Part lecture, part discussion, hands-on development and implementation, tests to gauge understanding Introduction Installing Berkeley DB Configuring Berkeley DB Database operations Working with the Berkeley DB API Creating transactional applications in Berkeley DB Creating concurrent data stores Cursor operations Querying the database Working with indexes Replicating your application Berkeley DB utilities Building, configuring and updating Berkeley DB Backup and recovery Tuning Berkeley DB
pythonmultipurpose Advanced Python 28小时 In this instructor-led training, participants will learn advanced Python programming techniques, including how to apply this versatile language to solve problems in areas such as distributed applications, finance, data analysis and visualization, UI programming and maintenance scripting. Audience Developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice Notes If you wish to add, remove or customize any section or topic within this course, please contact us to arrange.   Introduction     Python versatility: from data analysis to web crawling Python data structures and operations     Integers and floats     Strings and bytes     Tuples and lists     Dictionaries and ordered dictionaries     Sets and frozen sets     Data frame (pandas)     Conversions Object-oriented programming with Python     Inheritance     Polymorphism     Static classes     Static functions     Decorators     Other Data Analysis with pandas     Data cleaning     Using vectorized data in pandas     Data wrangling     Sorting and filtering data     Aggregate operations     Analyzing time series Data visualization     Plotting diagrams with matplotlib     Using matplotlib from within pandas     Creating quality diagrams     Visualizing data in Jupyter notebooks     Other visualization libraries in Python Vectorizing Data in Numpy     Creating Numpy arrays     Common operations on matrices     Using ufuncs     Views and broadcasting on Numpy arrays     Optimizing performance by avoiding loops     Optimizing performance with cProfile Processing Big Data with Python     Building and supporting distributed applications with Python     Data storage: Working with SQL and NoSQL databases     Distributed processing with Hadoop and Spark     Scaling your applications Python for finance     Packages, libraries and APIs for financial processing         Zipline         PyAlgoTrade         Pybacktest         quantlib         Python APIs Extending Python (and vice versa) with other languages     C#     Java     C++     Perl     Others Python multi-threaded programming     Modules     Synchronizing     Prioritizing UI programming with Python     Framework options for building GUIs in Python         Tkinter         Pyqt Python for maintenance scripting     Raising and catching exceptions correctly     Organizing code into modules and packages     Understanding symbol tables and accessing them in code     Picking a testing framework and applying TDD in Python Python for the web     Packages for web processing     Web crawling     Parsing HTML and XML     Filling web forms automatically Closing remarks
cpd200 CPD200: Developing Solutions on Google Cloud Platform 24小时 This 3 day instructor-led class introduces participants to Solution Development for Google Cloud Platform. Through a combination of instructor-led presentations, demonstrations, and hands-on labs, students learn how to develop cloud-based applications using Google App Engine, Google Cloud Datastore, and Google Cloud Endpoints. This class is intended for experienced application developers who want to learn how to develop solutions using Google Cloud Platform to create highly scalable backends for both web and mobile applications. At the end of this one­day course, participants will be able to: Manage Google Cloud Source Repositories using the Google Cloud Platform Console Test an App Engine application using the App Engine SDK Access the App Engine Development Server Console Create an API using Google Cloud Endpoints Test a Cloud Endpoint API using the API Explorer Deploy an application to App Engine using the App Engine SDK Design, structure and configure an App Engine application using multiple services Create Client IDs using the Google Cloud Platform Console Secure App Engine services and Cloud Endpoints APIs using authentication Configure and upload new versions of App Engine services Integrate Google Cloud Logging into App Engine applications Review quota usage in a Google Cloud Platform project Integrate different types of storage with App Engine applications Create and implement a data model for use with Google Cloud Datastore Implement a variety of queries in Google Cloud Datastore Update the index configuration in Google Cloud Datastore Implement transactions using Google Cloud Datastore Review Google Cloud Trace reports in the Google Cloud Platform Console Integrate the Memcache API into an App Engine application to increase performance Configure, run and review the output of Google Cloud Security Scanner Configure the scaling behaviour of individual App Engine Services Create App Engine handlers for Push Task Queues Send email from an App Engine application using the Mail API Schedule Tasks in App Engine using the Cron Service Update the configuration of the Cron Service Secure Task Push, and Cron Service handlers  Export Google Cloud Platform data from a project Delete Google Cloud Platform projects and resources   Module 1: Developing Solutions for Google Cloud Platform Identify the advantages of Google Cloud Platform for solution development Identify services and tools available for solution development using Google Cloud Platform Compare examples of Google Cloud Platform architectures for solution development Lab: Google Cloud Source Repositories Create a project for the course Use Google Cloud Shell to develop and test an application using the App Engine SDK  Configure Google Cloud Source Repositories to remotely host code in Google Cloud Platform Module 2: Google Cloud Endpoints Identify Cloud Endpoints features Explain how to develop APIs using Cloud Endpoints Compare development of Cloud Endpoints APIs using Java and Python Lab: Google Cloud Endpoints Review and edit Cloud Endpoints source code Deploy an application to App Engine Test a Cloud Endpoints  API in the APIs Explorer Module 3: App Engine Services Explain the use cases for App Engine Services and how to use them in structuring an application Identify how to deploy and access individual App Engine services Explain how to route requests to individual services Lab: Google App Engine Services Review the code for a sample application used throughout the remainder of the course Deploy multiple App Engine services to a single project Module 4: User Authentication and Credentials Compare authentication and authorization Identify options for securing App Engine applications Explain the use cases for Application Default Credentials Lab: User Authentication Configure the OAuth consent screen and create a client ID Modify Conference Central to use your client ID Test Conference Central authentication Modify your admin service to require administrator rights Module 5: Managing App Engine Applications Explain the use cases for App Engine versions Identify how to access App Engine monitoring and logging services Explain the use of resource quotas and how to troubleshoot related errors Lab: Managing Google App Engine Applications Review App Engine settings, quotas, instances, and logs Update App Engine services to log to Cloud Logging Deploy new versions of your default and admin services Route all traffic to a new version of the default service Module 6: Storage for Solution Developers Compare storage options for App Engine Solutions Developers Explain the purpose of, and use cases for, Google Cloud Storage Compare Cloud SQL integration with App Engine and Compute Engine Explain basic Cloud Datastore terminology and concepts, including Entity Groups Lab: Google Cloud Datastore Update an existing application to save data persistently Test saving application data to Cloud Datastore List and view Cloud Datastore entities in the Google Cloud Platform Console Module 7: Queries and Indexes Identify available query filters for Cloud Datastore Compare single­property, and composite indexes in Cloud Datastore Configure and optimize indexes for Cloud Datastore Lab: Google Cloud Datastore Queries and Indexes Add support for querying entities by kind and ancestor Add query filters to Cloud Datastore searches Update an index configuration to support composite indexes Module 8: Entity Groups, Consistency, and Transactions Identify the steps of a Cloud Datastore write Compare strong and eventual consistency in Cloud Datastore Identify how to achieve strongly consistent queries Identify best practises for Cloud Datastore transactions Lab: Google Cloud Datastore Transactions Add support for using Cloud Datastore transactions to an application Add a Cloud Endpoint API method to view data from a different service Module 9: App Engine Performance and Optimization Identify Memcache types, use cases, and implementation patterns Compare available scaling behaviours for application services Configure application scaling for individual services Lab: Google App Engine Performance and Optimization Review Cloud Trace reports for an application Configure and run a security scan for an application Update an application to make use of memcache Configure and test application scaling for application services Module 10: Task Queues Compare Push and Pull Queues Explain how to schedule tasks with the Cron Service Configure and securing Push and Pull Queues, as well as the Cron Service Lab: Task Queue API Add a task handler to send an email using the Mail API Add a Cron Service handler and configuration to an existing application Lab: Deleting Google Cloud Platform Projects and Resources Export Google Cloud Platform data from a project Delete Google Cloud Platform resources Shut down a Google Cloud Platform project
accumulo Apache Accumulo: Building highly scalable big data applications 21小时 Apache Accumulo is a sorted, distributed key/value store that provides robust, scalable data storage and retrieval. It is based on the design of Google's BigTable and is powered by Apache Hadoop, Apache Zookeeper, and Apache Thrift.   This courses covers the working principles behind Accumulo and walks participants through the development of a sample application on Apache Accumulo. Audience     Application developers     Software engineers     Technical consultants Format of the course     Part lecture, part discussion, hands-on development and implementation, occasional tests to gauge understanding Introduction Installing Accumulo Configuring Accumulo Understanding Accumulo's data model, architecture, and components Working with the shell Database operations Configuring your tables Accumulo iterators Developing an application in Accumulo Securing your application Reading and writing secondary indexes Working with Mapreduce, Spark, and Thrift Proxy Testing your application Troubleshooting Deploying your application Accumulo Administrative tasks
PentahoDI Pentaho Data Integration Fundamentals 21小时 Pentaho Data Integration is an open-source data integration tool for defining jobs and data transformations. In this instructor-led, live training, participants will learn how to use Pentaho Data Integration's powerful ETL capabilities and rich GUI to manage an entire big data lifecycle, maximizing the value of data to the organization. By the end of this training, participants will be able to: Create, preview, and run basic data transformations containing steps and hops Configure and secure the Pentaho Enterprise Repository Harness disparate sources of data and generate a single, unified version of the truth in an analytics-ready format. Provide results to third-part applications for further processing Audience Data Analyst ETL developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
hivehiveql Data Analysis with Hive/HiveQL 7小时 This course covers how to use Hive SQL language (AKA: Hive HQL, SQL on Hive, HiveQL) for people who extract data from Hive Hive Overview Architecture and design Aata types SQL support in Hive Creating Hive tables and querying Partitions Joins Text processing labs : various labs on processing data with Hive DQL (Data Query Language) in Detail SELECT clause Column aliases Table aliases Date types and Date functions Group function Table joins JOIN clause UNION operator Nested queries Correlated subqueries
druid Druid: Build a fast, real-time data analysis system 21小时 Druid is an open-source, column-oriented, distributed data store written in Java. It was designed to quickly ingest massive quantities of event data and execute low-latency OLAP queries on that data. Druid is commonly used in business intelligence applications to analyze high volumes of real-time and historical data. It is also well suited for powering fast, interactive, analytic dashboards for end-users. Druid is used by companies such as Alibaba, Airbnb, Cisco, eBay, Netflix, Paypal, and Yahoo. In this course we explore some of the limitations of data warehouse solutions and discuss how Druid can compliment those technologies to form a flexible and scalable streaming analytics stack. We walk through many examples, offering participants the chance to implement and test Druid-based solutions in a lab environment. Audience     Application developers     Software engineers     Technical consultants     DevOps professionals     Architecture engineers Format of the course     Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding Introduction Installing and starting Druid Druid architecture and design Real-time ingestion of event data Sharding and indexing Loading data Querying data Visualizing data Running a distributed cluster Druid + Apache Hive Druid + Apache Kafka Druid + others Troubleshooting Administrative tasks
hdp Hortonworks Data Platform (HDP) for administrators 21小时 Hortonworks Data Platform is an open-source Apache Hadoop support platform that provides a stable foundation for developing big data solutions on the Apache Hadoop ecosystem. This instructor-led live training introduces Hortonworks and walks participants through the deployment of Spark + Hadoop solution. By the end of this training, participants will be able to: Use Hortonworks to reliably run Hadoop at a large scale Unify Hadoop's security, governance, and operations capabilities with Spark's agile analytic workflows. Use Hortonworks to investigate, validate, certify and support each of the components in a Spark project Process different types of data, including structured, unstructured, in-motion, and at-rest. Audience Hadoop administrators Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.  
sqlmysql SQL in MySQL 14小时 How to build a query? What opportunities has the SQL in a MySQL database? What is a relational database? What is the structure and SQL commands? Relational database models Relational operators Characteristics of declarative SQL language SQL syntax Division language DQL, DML, DDL, DCL Data Query Language SELECT queries. Aliases columns of tables Service date (DATE types, display functions, formatting) Group Features Combining internal and external tables (JOIN clause) UNION operator Nested Subqueries (the WHERE clause, the table name, column name) Correlated subqueries Data Modification Language Inserting rows (INSERT clause) Inserting rows by request Variation of the rows (UPDATE) Delete rows (DELETE) Data Definition Language Creating, altering and dropping objects (CREATE, ALTER, DROP) Creating tables using subquery (CREATE TABLE .... AS SELECT...) CONSTRAINTS Options NULL and NOT NULL CONSTRAINT clause ENUM type type SET PRIMARY KEY condition UNIQUE condition FOREIGN KEY condition DEFAULT clause Transactions The command COMMIT, ROLLBACK, SAVEPOINT
Imp Impala for Business Intelligence 21小时 Cloudera Impala is an open source massively parallel processing (MPP) SQL query engine for Apache Hadoop clusters. Impala enables users to issue low-latency SQL queries to data stored in Hadoop Distributed File System and Apache Hbase without requiring data movement or transformation. Audience This course is aimed at analysts and data scientists performing analysis on data stored in Hadoop via Business Intelligence or SQL tools. After this course delegates will be able to Extract meaningful information from Hadoop clusters with Impala. Write specific programs to facilitate Business Intelligence in Impala SQL Dialect. Troubleshoot Impala. Introduction to Impala What is Impala? How Impala Differs from Relational Databases Limitations and Future Directions Using the Impala Shell The Impala Daemon, Statestore and Catalogue service Loading Impala Explore a New Impala Instance Load CSV Data from Local Files Point an Impala Table at Existing Data Files Analyzing Data with Impala Describe the Impala Table Basic Syntax and Querying Data Types Filtering, Sorting, and Limiting Results Joining and Grouping Data Data Loading and Querying Examples Improving Impala Performance How Impala works with Hadoop file formats Hands-On Exercise: Interactive Analysis with Impala Programming Impala Applications Overview of the Impala SQL Dialect Overview of Impala Programming Interfaces Troubleshooting Impala Troubleshooting Impala SQL Syntax Issues Troubleshooting I/O Capacity Problems Impala Web User Interface for Debugging    
nlpwithr NLP: Natural Language Processing with R 21小时 It is estimated that unstructured data accounts for more than 90 percent of all data, much of it in the form of text. Blog posts, tweets, social media, and other digital publications continuously add to this growing body of data. This course centers around extracting insights and meaning from this data. Utilizing the R Language and Natural Language Processing (NLP) libraries, we combine concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically understand the meaning behind text data. Data samples are available in various languages per customer requirements. By the end of this training participants will be able to prepare data sets (large and small) from disparate sources, then apply the right algorithms to analyze and report on its significance. Audience     Linguists and programmers Format of the course     Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding Introduction     NLP and R vs Python Installing and configuring R Studio Installing R packages related to Natural Language Processing (NLP). An overview of R’s text manipulation capabilities Getting started with an NLP project in R Reading and importing data files into R Text manipulation with R Document clustering in R Parts of speech tagging in R Sentence parsing in R Working with regular expressions in R Named-entity recognition in R Topic modeling in R Text classification in R Working with very large data sets Visualizing your results Optimization Integrating R with other languages (Java, Python, etc.) Closing remarks
zeppelin Zeppelin for interactive data analytics 14小时 Apache Zeppelin is a web-based notebook for capturing, exploring, visualizing and sharing Hadoop and Spark based data. This instructor-led, live training introduces the concepts behind interactive data analytics and walks participants through the deployment and usage of Zeppelin in a single-user or multi-user environment. By the end of this training, participants will be able to: Install and configure Zeppelin Develop, organize, execute and share data in a browser-based interface Visualize results without referring to the command line or cluster details Execute and collaborate on long workflows Work with any of a number of plug-in language/data-processing-backends, such as Scala ( with Apache Spark ), Python ( with Apache Spark ), Spark SQL, JDBC, Markdown and Shell. Integrate Zeppelin with Spark, Flink and Map Reduce Secure multi-user instances of Zeppelin with Apache Shiro Audience Data engineers Data analysts Data scientists Software developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.  
mysqladm MySQL Database Administration 14小时 MySQL Administration training course is for anyone who wants to administrate the MySQL database server. It is a comprehensive course covering all administrator duties. The course explains how MySQL Database works, what tools are available, how we can use them, how we can secure the MySQL Database Server and configure it. During the training course you will learn how to manage user accounts and how the MySQL Access Privilege System works. You also will learn how to maintain your database, backup and recover your databases and perform crash recovery. MySQL Server Files and Scripts MySQL Programs MySQL Server MySQL Client GUI Tools MySQL Server Configuration mysqld Options The Server SQL Mode Server System Variables Dynamic System Variables Server Status Variables Shutdown Process MySQL Security Issues Securing MySQL Against Attacks Security-Related mysqld Options Security Issues with LOAD DATA LOCAL MySQL Access Privilege System MySQL Privilege System Overview Privileges Provided by MySQL Connecting to the MySQL Server - Stages Access Control, Stage 1: Connection Verification Access Control, Stage 2: Request Verification Access Denied Errors MySQL User Account Management Users and Passwords Creating New Users Deleting User Accounts Limiting User Resources Changing Passwords MySQL Database Maintenance Backup and Recovery Point-in-Time Recovery Maintenance and Crash Recovery myisamchk Syntax and Options Getting Table Information MySQL Local Setting National Characters and Sorting MySQL Server Time Zone MySQL Log Files Error Log General Query Log Update Log Binary Log Slow Query Log Log File Maintenance and Rotation Running Multiple MySQL Servers on the Same Machine Running Multiple Servers in Windows Running Multiple Servers in Windows as Services Running Multiple Servers in Unix and Linux Using Client Tools in a Multi-Server Environment MySQL Query Cache The Concept of Query Cache Testing Query Cache with SELECT Configuring Query Cache Checking Query Cache Status and Maintenance
osqlint Oracle SQL Intermediate 14小时 Audience All who want to improve their basic skills in Oracle SQL and also systematize already gained knowledge. Format of the course 25% lectures, 75% labs Create complex queries to databases Use available operators Queries with multiple conditions Creating tables and references DDL commands (create, alter, and drop) Create referential integrity Normalization of tables (up to 3 normal form) anomalies and ways to avoid them Changes in the structure of existing tables ALTER clause Manipulation of data DML commands (insert, update, delete) Creating new users and granting permissions DCL commands (grant, revoke) Linking Tables Internal and external joins Data Aggregation Features of grouping functions Use the GROUP BY clause and HAVING Grouping multiple column Subqueries multi-column correlated WITH clause
seqdb SequoiaDB for Developers 14小时 SequoiaDB is a document-oriented NewSQL database that supports JSON transaction processing and SQL query. SequoiaDB can directly interface with applications to provide high performance and horizontally scalable data storage and processing functions, or serve as the frontend to Hadoop and Spark for both real-time query and data analysis. Audience This course assumes prior knowledge of SQL and is targeted at engineers seeking to deploy and integrate SequoiaDB instances. After completing this course, delegates will: understand SequoiaDB’s structure and deployment mechanisms be able to carry out installation / production environment / architecture tasks and configuration be able to assess code quality, perform debugging, monitoring be able to implement advanced production like integration, migration and development Using SequoiaDB Starting SequoiaDB Connectors (Hadoop/Hive/Map Reduce) Basic Operators with reference Developing for SequoiaDB Data Models SequoiaDB Shell SQL to SequiaDB mapping Aggregation Reference Operator SequoiaDB Shell SQL to SequoiaDB mapping list Error List
voldemort Voldemort: Setting up a key-value distributed data store 14小时 Voldemort is an open-source distributed data store that is designed as a key-value store.  It is used at LinkedIn by numerous critical services powering a large portion of the site. This course will introduce the architecture and capabilities of Voldomort and walk participants through the setup and application of a key-value distributed data store. Audience     Software developers     System administrators     DevOps engineers Format of the course     Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding Introduction Understanding distributed key-value storage systems Voldomort data model and architecture Downloading and configuration Command line operations Clients and servers Working with Hadoop Configuring build and push jobs Rebalancing a Voldemort instance Serving Large-scale Batch Computed Data Using the Admin Tool Performance tuning
meanangular4 Angular 4: Building Web Apps using the MEAN stack 35小时 Angular 4 (previous versions referred to as: Angular.js, AngularJS, AngularJS 1, Angular 1, Angular 2, etc.) is a JavaScript-based front-end web application framework for developing single-page applications. It boasts better performance over its predecessor, more APIs to tap into, and improved design and responsiveness on mobile devices. MEAN stack is a full-stack JavaScript solution for writing scalable, robust, and maintainable web applications quickly and easily using MongoDB, Express, Angular, and Node.js. In this instructor-led, live training, participants will learn how to use the MEAN stack, specifically using Angular 4, as they step through the creation and deployment of a sample web application. By the end of this training, participants will be able to: Create, build, debug and deploy a MEAN-based Angular 4 application Unit test their Angular 4 application Write Angular code using TypeScript Audience Developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.  
sqlfun SQL Fundamentals 14小时 This SQL training course is for people who want to gain the necessary skills to extract and analyse data from any database and create reports. Course members will learn: how to write SQL queries what relational databases are and how we can use them what are relations and how to create them the structure of data differences between SQL dialects (Oracle, T-SQL, ANSI) practical skills for writing queries This SQL course deals with generic ANSI SQL. It can be used in any database, including Oracle, MySQL, Microsoft Access, Microsoft SQL Server, DB2, Informix, PostgreSQL any other relational databases. RDBMS (Relational DataBase Management System) Relational Operators SQL as Declarative Language SQL Syntax SQL Sublanguages DQL, DML, DDL, DCL DQL (Data Query Language) in Detail SELECT clause Column aliases Table aliases Date types and Date functions Group function Table joins JOIN clause UNION operator Nested queries Correlated subqueries DML (Data Manipulation Language) Overview Inserting rows (INSERT) Inserting rows using subquery Updating rows (UPDATE) Deleting rows (DELETE) DDL (Data Definition Language) Overview Creating, altering and dropping objects (CREATE, ALTER, DROP) Creating tables using subquery (CREATE TABLE .... AS SELECT...) CONSTRAINTS Overview NULL i NOT NULL CONSTRAINT clause ENUM type SET type PRIMARY KEY UNIQUE FOREIGN KEY DEFAULT clause Transactions Overview COMMIT ROLLBACK SAVEPOINT Implicit and explicit rollbacks and commits SQL Dialects Overview MySQL Microsoft Access and SQL Server Oracle and PostgreSQL
hadoopmapr Hadoop Administration on MapR 28小时 Audience: This course is intended to demystify big data/hadoop technology and to show it is not difficult to understand. Big Data Overview: What is Big Data Why Big Data is gaining popularity Big Data Case Studies Big Data Characteristics Solutions to work on Big Data. Hadoop & Its components: What is Hadoop and what are its components. Hadoop Architecture and its characteristics of Data it can handle /Process. Brief on Hadoop History, companies using it and why they have started using it. Hadoop Frame work & its components- explained in detail. What is HDFS and Reads -Writes to Hadoop Distributed File System. How to Setup Hadoop Cluster in different modes- Stand- alone/Pseudo/Multi Node cluster. (This includes setting up a Hadoop cluster in VirtualBox/KVM/VMware, Network configurations that need to be carefully looked into, running Hadoop Daemons and testing the cluster). What is Map Reduce frame work and how it works. Running Map Reduce jobs on Hadoop cluster. Understanding Replication , Mirroring and Rack awareness in context of Hadoop clusters. Hadoop Cluster Planning: How to plan your hadoop cluster. Understanding hardware-software to plan your hadoop cluster. Understanding workloads and planning cluster to avoid failures and perform optimum. What is MapR and why MapR : Overview of MapR and its architecture. Understanding & working of MapR Control System, MapR Volumes , snapshots & Mirrors. Planning a cluster in context of MapR. Comparison of MapR with other distributions and Apache Hadoop. MapR installation and cluster deployment. Cluster Setup & Administration: Managing services, nodes ,snapshots, mirror volumes and remote clusters. Understanding and managing Nodes. Understanding of Hadoop components, Installing Hadoop components alongside MapR Services. Accessing Data on cluster including via NFS Managing services & nodes. Managing data by using volumes, managing users and groups, managing & assigning roles to nodes, commissioning decommissioning of nodes, cluster administration and performance monitoring, configuring/ analyzing and monitoring metrics to monitor performance, configuring and administering MapR security. Understanding and working with M7- Native storage for MapR tables. Cluster configuration and tuning for optimum performance. Cluster upgrade and integration with other setups: Upgrading software version of MapR and types of upgrade. Configuring Mapr cluster to access HDFS cluster. Setting up MapR cluster on Amazon Elastic Mapreduce. All the above topics include Demonstrations and practice sessions for learners to have hands on experience of the technology.
couch Apache CouchDB for Developers 14小时 Adobe CouchDB is a scalable, fault-tolerant, and schema-free document-oriented database written in Erlang. It's used in large and small organizations for a variety of applications where a traditional SQL database isn't the best solution for the problem at hand. Audience This course is directed at engineers and developers seeking to deploy and develop with a CouchDB instance. Installing CouchDB Introduction: CouchDB at a glance  Installation: Get up and running fast  Technical Overview: Details of the CouchDB technology  Basics: Getting started with CouchDB  Configuring CouchDB Base Configuration couch_peruser CouchDB HTTP Server Authentication and Authorization Compaction Configuration Logging Replicator Query Servers External Processes HTTP Resource Handlers CouchDB Internal Services Miscellaneous Parameters Proxying Configuration CouchApp CouchDB External APIs Query Server Fauxton  Cluster Setup Theory Node Management Database Management Sharding JSON Structure All Database Documents Bulk Documents Troubleshooting Breaking Changes Error Messages Known Problem Official CouchDB bug tracker
meteor Meteor: Use JavaScript to develop cross-platform mobile applications 14小时 Meteor (aka MeteorJS) is an open-source JavaScript web framework written in Node.js. It integrates with MongoDB and enables rapid prototyping of Android and iOS applications. This course introduces the fundamentals of Meteor and walks participants through the creation of a real-time web applications for both desktop and mobile platforms. Audience     Front-end developers     Anyone interested in learning Meteor Format of the course     Overview of Meteor's features and capabilities along with step-by-step development of a mobile application for iOS and Android. Introduction to Meteor JavaScript Installing Meteor Meteor architecture Overview of MongoDB Creating a Meteor application Meteor's project file structure Creating a Template and Collections Working with Forms and Events Sessions and Trackers in Meteor Working with the the Core API Working with HTTP, Email, Assets Creating a database in Meteor Building database collections Sorting the data in Meteor Building a user accounts system Creating packages in Meteor Deploying your application
ApacheIgnite Apache Ignite: Improve speed, scale and availability with in-memory computing 14小时 Apache Ignite is an in-memory computing platform that sits between the application and data layer to improve speed, scale and availability. In this instructor-led, live training, participants will learn the principles behind persistent and pure in-memory storage as they step through the creation of a sample in-memory computing project. By the end of this training, participants will be able to: Use Ignite for in-memory, on-disk persistence as well as a purely distributed in-memory database Achieve persistence without syncing data back to a relational database Use Ignite to carry out SQL and distributed joins Improve performance by moving data closer to the CPU, using RAM as a storage Spread data sets across a cluster to achieve horizontal scalability Integrate Ignite with RDBMS, NoSQL, Hadoop and machine learning processors Audience Developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
sqlmysqladv SQL Advanced in MySQL 7小时 This course has been created for people already acquainted with SQL. The course introduces you into secrets common to all SQL databases as well as MySQL specific syntax, functions and features. DQL (Data Query Language) Correlation in FROM, WHERE, SELECT and HAVING clauses Correlation and performance Using CASE, IF, COALESCE functions Using variables Casting and converting Dealing with NULL, NULL-safe operators Using regular expression with REGEXP operator Useful MySQL specific group by functions (GROUP_CONCAT, etc.) GROUP BY WITH ROLLUP EXISTS, ALL, ANY Multitable OUTER JOIN Rewriting subqueries as joins DML (Data Modification Language) Multi-row inserts INSERT by SELECT Using subqueries in DML statements Using variables in DML queries Locking tables and rows Updating data in many tables IGNORE clause REPLACE clause DELETE versus TRUNCATE DDL (Data Definition Language) Creating tables with select Temporary tables Stored Procedures Short introduction to MySQL stored procedures
mariadbgc MariaDB Galera Cluster Administration 21小时 This course is intended for database administrators. The course presents options for High-Availability solutions using Galera Cluster. You will learn the basics of Galera technology, as well as more advanced topics and practical knowledge related to configuring, optimizing and administering a Galera Cluster. Topic overview Why I need them and what are High-Availability solutions? Cluster concepts ​What is MariaDB Galera Cluster and what it offers to my organization? Galera Cluster Management How to start with Galera - what should I now before installation? Architecture and functionality First steps - Installation Going deeper - Configuration and Set-up Almost like a pro - Administration Performance Operations and operation modes Upgrade Galera Backups and restoring ​Controlling state transfer between nodes Load balancing Monitoring How to deal with Galera multi- master configuration Advanced features Security Scalability Replication ​Advanced configuration
ddavsvbsqls Developing Desktop Applications with Visual Studio 2012, VB.NET and SQL Server 2012 21小时 This course is divided into 3 main sections and is made up of a mixture of presentations and practical exercises. VB.NET Language in Visual Studio 2012 VB.NET Object Orientation VB.NET and Sql Server 2012 Part I. VB.NET Language in Visual Studio 2012 Module 1. Introduction to Visual Basic 2012 The Object-Oriented Programming The Visual Studio 2012 IDE Creating a new Application Using the Help System Module 2. The Microsoft .NET Framework The .NET Framework Classes Executing the Code Common Language Runtime Code Loading and Execution Application Isolation Security Interoperability Exception Handling Module 3. The Visual Basic 2012 Language Data Types Storing Variables Using Methods Making Decisions Working with Data Structures Using Arrays, Enumerations and Collections Module 4. Building Windows Applications Responding to Events Creating the Toolbar Creating the Status Bar Using Multiple Forms OpenFileDialog and SaveDialog controls PrintDialog and FolderBrowserDialog controls Understanding Menu Features Creating Menus Context Menus Part II. VB.NET Object Orientation Module 5. Building Objects Understanding Objects Encapsulation Methods and Properties Managing Events Building Classes Using Constructors Managing Inheritance Module 6. Advanced Language Constructs Using Lambda Expressions Using Async and Wait Using Iterators Module 7. Exception Handling and Debugging Handling Exceptions Try, Catch, Finally The Throw Keyword The Exit Try Statement Using Exit Try Statement Using Exception Properties Logging Errors Module 8. Parallel Programming Using Tasks and Threads Launching Parallel Tasks Transforming Sequential Code to Parallel Code Parallelizing Loops Specifying the Desired Degree of Parallelism Creating and Managing Tasks Part III. VB.NET and Sql Server 2012 Module 9. Database Programming with Sql Server 20012 and ADO.NET The ADO.NET architecture The Connection class The Command and DataReader Classes The ExecuteReader(), ExecuteScalar(), ExecuteNonQuery() methods Using Parameterized Commands Calling Stored Procedure Managing Transactions Module 10. Data Components and the DataSet Building a Data Access Component Managing Disconnected Data The DataSet Class The DataAdapter Class: Filling a DataSet, working with Multiple Tables and Relationships The DataView Class Module 11. Using Data Binding Basic Data Binding Data Source Controls The SqlDataSource Inserting, Updating, Deleting and Selecting records
BigData_ A practical introduction to Data Analysis and Big Data 35小时 Participants who complete this training will gain a practical, real-world understanding of Big Data and its related technologies, methodologies and tools. Participants will have the opportunity to put this knowledge into practice through hands-on exercises. Group interaction and instructor feedback make up an important component of the class. The course starts with an introduction to elemental concepts of Big Data, then progresses into the programming languages and methodologies used to perform Data Analysis. Finally, we discuss the tools and infrastructure that enable Big Data storage, Distributed Processing, and Scalability. Audience Developers / programmers IT consultants Format of the course     Part lecture, part discussion, hands-on practice and implementation, occasional quizing to measure progress. Introduction to Data Analysis and Big Data What makes Big Data "big"? Velocity, Volume, Variety, Veracity (VVVV) Limits to traditional Data Processing Distributed Processing Statistical Analysis Types of Machine Learning Analysis Data Visualization Languages used for Data Analysis R language Why R for Data Analysis? Data manipulation, calculation and graphical display Python Why Python for Data Analysis? Manipulating, processing, cleaning, and crunching data Approaches to Data Analysis Statistical Analysis Time Series analysis Forecasting with Correlation and Regression models Inferential Statistics (estimating) Descriptive Statistics in Big Data sets (e.g. calculating mean) Machine Learning Supervised vs unsupervised learning Classification and clustering Estimating cost of specific methods Filtering Natural Language Processing Processing text Understaing meaning of the text Automatic text generation Sentiment/Topic Analysis Computer Vision Acquiring, processing, analyzing, and understanding images Reconstructing, interpreting and understanding 3D scenes Using image data to make decisions Big Data infrastructure Data Storage Relational databases (SQL) MySQL Postgres Oracle Non-relational databases (NoSQL) Cassandra MongoDB Neo4js Understanding the nuances Hierarchical databases Object-oriented databases Document-oriented databases Graph-oriented databases Other Distributed Processing Hadoop HDFS as a distributed filesystem MapReduce for distributed processing Spark All-in-one in-memory cluster computing framework for large-scale data processing Structured streaming Spark SQL Machine Learning libraries: MLlib Graph processing with GraphX Scalability Public cloud AWS, Google, Aliyun, etc. Private cloud OpenStack, Cloud Foundry, etc. Auto-scalability Choosing right solution for the problem The future of Big Data Closing remarks
datameer Datameer for Data Analysts 14小时 Datameer is a business intelligence and analytics platform built on Hadoop. It allows end-users to access, explore and correlate large-scale, structured, semi-structured and unstructured data in an easy-to-use fashion. In this instructor-led, live training, participants will learn how to use Datameer to overcome Hadoop's steep learning curve as they step through the setup and analysis of a series of big data sources. By the end of this training, participants will be able to: Create, curate, and interactively explore an enterprise data lake Access business intelligence data warehouses, transactional databases and other analytic stores Use a spreadsheet user-interface to design end-to-end data processing pipelines Access pre-built functions to explore complex data relationships Use drag-and-drop wizards to visualize data and create dashboards Use tables, charts, graphs, and maps to analyze query results Audience Data analysts Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
advsqlpt Advanced SQL, Stored Procedures and Triggers for Microsoft SQL Server 14小时 The aim of this course is to provide a clear understanding of the advanced use of (SQL) for Microsoft SQL Server and the advanced use of Transact-SQL. For more in depth coverage of the topics this course can be run as a three day course. Review of Structured Query Language DQL, DML, DDL The GROUP BY, HAVING Clause Sub-queries and Correlated Sub-queries Advanced Update & Delete Statements Sub-queries Correlated Sub-queries Procedural Programming Variables Control-Of-Flow Statements IF, WHILE, CASE, GOTO, RETURN Managing Errors Responding To Errors RAISERROR PRINT Using Transactions Introduction To Transactions Transaction Isolation Levels Deadlocks Transactional Error Handling Implementing Cursors Declaring Cursors OPEN, FETCH, CLOSE DEALLOCATE CURRENT OF Stored Procedures Creating Stored Procedures Passing values into a Stored Procedure Returning Information From Stored Procedures Altering Stored Procedures Triggers Creating Triggers Transactional Error Handling Using Inserted and Deleted Tables
cassdbfun Fundamentals of Cassandra DB 21小时 This course introduces the basics of Cassandra 2.0 including its installation & configuration, internal architecture, tools, Cassandra Query Language, and administration. Audience Administrators and developers seeking to use Cassandra. This course serves as a foundation and prerequisite for other advanced Cassandra courses.   Introduction to Cassandra Big Data Common use cases of Cassandra Cassandra architecture Installation and Configuration Running and Stopping Cassandra instance Cassandra Data Model Cassandra Query Language Configuring the Cassandra nodes and clusters using CCM cqlsh shell commands nodetool Using cassandra-stress to populate and test the Cassandra nodes Coordinating the Cassandra requests Replication Consistency Tuning Cassandra Nodes Communication Writing and Reading data to/from the storage engine Data directories Anti-entropy operations Cassandra Compaction Choosing and Implementing compaction strategies Best practices in hardware planning Troubleshooting resources
aerosdev Aerospike for Developers 14小时 This course covers everything a database developer needs to know to successfully develop applications using Aerospike.Data Management Data Model Primary Index Secondary Index Hybrid Storage Distribution Data Distribution Consistency Guarantees Clustering Cross Data-Center Replication Rack Awareness Client Architecture ACID Key-Value Store Single Record Batch Scans Policies Data Types Lists Maps Geospatial Large Data Types Query User-Defined Functions Record UDF Stream UDF Aggregation Security (Enterprise Edition only) Known Limitations
elasticsearchfordevs ElasticSearch for developers: building search and analytics solutions with Elasticsearch 14小时 Elasticsearch is an open-source, distributed search engine. It is commonly used together with Logstash (data-collection and log-parsing engine) and Kibana (analytics and visualization platform) to make up the the "ELK stack". This training is aimed at software developers who wish to build search and analytics solutions using Elasticsearch The training starts with a discussion of the ElastickSearch architecture, including its distributed model and search API. This is followed by an explanation of ElasticSearch's functionality and how to best integrate it into your own application. Hands-on exercises make up an important part of the training, and give participants a chance to put into practice their knowledge while receiving feedback on their implementation and progress. Audience     Software developers Format of the course      Heavy emphasis on live practice. Most of the concepts are learned through samples, exercises and hands-on development. Introduction to Elasticsearch Writing search queries Performing text analysis Defining mappings Expanding your searches The distributed model Manipulating search results Performing aggregations Handling data relationships Closing remarks
deckgl deck.gl: Visualizing Large-scale Geospatial Data 14小时 deck.gl is an open-source, WebGL-powered library for exploring and visualizing data assets at scale. Created by Uber, it is especially useful for gaining insights from geospatial data sources, such as data on maps. This instructor-led, live training introduces the concepts and functionality behind deck.gl and walks participants through the set up of a demonstration project. By the end of this training, participants will be able to: Take data from very large collections and turn it into compelling visual representations Visualize data collected from transportation and journey-related use cases, such as pick-up and drop-off experiences, network traffic, etc. Apply layering techniques to geospatial data to depict changes in data over time Integrate deck.gl with React (for Reactive programming) and Mapbox GL (for visualizations on Mapbox based maps). Understand and explore other use cases for deck.gl, including visualizing points collected from a 3D indoor scan, visualizing machine learning models in order to optimize their algorithms, etc. Audience Developers Data scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
sqlsqlsvr SQL in SQL Server 14小时 This SQL training course is for people who want to gain the necessary skills to extract and analyse data from any database and create reports. Course members will learn: how to write SQL queries what relational databases are and how we can use them what are relations and how to create them the structure of data differences between T-SQL and other dialects practical skills for writing queries This SQL course deals with Microsoft T-SQL dialect. If you are interested in generic SQL, please see SQL Fundamentals course. RDBMS (Relational DataBase Management System) Relational Operators SQL as Declarative Language SQL Syntax SQL Sublanguages DQL, DML, DDL, DCL DQL (Data Query Language) in Detail SELECT clause Column aliases Table aliases Date types and Date functions Group function Table joins JOIN clause UNION operator Nested queries Correlated subqueries DML (DataManipulationLanguage) Overview Inserting rows (INSERT) Inserting rows using subquery Updating rows (UPDATE) Deleting rows (DELETE) DDL (Data Definition Language) Overview Creating, altering and dropping objects (CREATE, ALTER, DROP) Creating tables using subquery (CREATE TABLE .... AS SELECT...) CONSTRAINTS Overview NULL i NOT NULL CONSTRAINT clause ENUM type SET type PRIMARY KEY UNIQUE FOREIGN KEY DEFAULT clause Transactions Overview COMMIT ROLLBACK SAVEPOINT Implicit and explicit rollbacks and commits T-SQL Dialects Overview What is Transact-SQL T-SQL and portability with other dialects (what to avoid) Handling Date
transsqladv Transact SQL Advanced 7小时 Delegates will gain an understanding of some of the more advanced features of Transact SQL as well as being able to do each of the following: Use queries to return complex result sets Manage database objects to aid query performance Tune queries to perform more efficiently This course is for anyone who currently uses Transact SQL to extract data from a Microsoft SQL Server database and wishes to expand their knowledge particularly in the areas of data analysis and improving query speed. Analytical Functions Use of advanced summary functions Use of hierarchical queries Use of analytical summary functions, e.g. moving averages, running totals Use of ranking functions Useful Database Objects Principles of using indexes How to create and maintain an index Use of clustered tables Use of partitioned tables Use of metadata in the master database Query Performance Tracing Principles of query execution and optimisation Use of Execution Plan Use of table & index statistics Use of hints Basic Data Warehouse Techniques Use of Indexed Views Use of Dimension & fact tables Use of Star & Snowflake designs
redisadev Redis for Developers and System Administrators 14小时 Redis is an open source (BSD licensed), in-memory data structure store, used as database, cache and message broker.Day 1: developer topics Redis Releases Installation Configuration Starting Redis Redis client libraries and language bindings Redis data types and commands to manipulate them Strings List, Sets & Sorted sets Hashes Bit arrays HyperLogLogs Redis Pub/Sub Expiration Redis transactions & Lua scripts Performance tips Benchmarking Redis Commands to avoid Pipelining Memory optimization Mass insertion Day 2: advanced usage and sysadmin topics Partitioning Data organization tips Distributed locks Master-slave replication Redis Cluster Persistence Security Starting multiple instances of Redis Connection limits, timeouts & other safeguards High availability Latency monitoring
teraintro Teradata Fundamentals 21小时 Teradata is one of the popular Relational Database Management System. It is mainly suitable for building large scale data warehousing applications. Teradata achieves this by the concept of parallelism.  This course introduces the delegates to Teradata Introduction to Teradata Background Why use Teradata User Scalability Relational Concepts Introduction to RDBMS  Warehousing Concepts Set Up and Installation Installation Tools and Utilities like BTEQ Teradata Architecture Components Node Parsing Engine Message Parsing Layer - BYNET Access Module Processor Storage Architecture Retrieval Architecture Architectural Overview Teradata Basic Concepts - SQL Data Type Tables Permanent Volatile Global Temporary Derived Set v/s Multiset Tables Playing with Data - CRUD Operations [DDL and DML] Logical and Conditional Operators SET Operators String Manipulation Date/Time Built in and Aggregate Functions Joins and Subqueries Indexes Primary Secondary Teradata Advanced Concepts Case Coalesce Macros Stored Procedures Space Temp Spool Permanent Join Strategies Statistics Compression Hashing Algorithm OLAP Functions User Management Teradata Additional Concepts Utilities FastLoad MultiLoad FastExport BTEQ Data Protection Methodologies Optimization Strategies Note: The Training would be a mix of theory and handson, and it would be helpful if the delegates actively particpate in the given exercises.
embeddingprojector Embedding Projector: Visualizing your Training Data 14小时 Embedding Projector is an open-source web application for visualizing the data used to train machine learning systems. Created by Google, it is part of TensorFlow. This instructor-led, live training introduces the concepts behind Embedding Projector and walks participants through the setup of a demo project. By the end of this training, participants will be able to: Explore how data is being interpreted by machine learning models Navigate through 3D and 2D views of data to understand how a machine learning algorithm interprets it Understand the concepts behind Embeddings and their role in representing mathematical vectors for images, words and numerals. Explore the properties of a specific embedding to understand the behavior of a model Apply Embedding Project to real-world use cases such building a song recommendation system for music lovers Audience Developers Data scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
oplsqlfun ORACLE PL/SQL Fundamentals 21小时 This 3 day course gives an introduction to ORACLE PL/SQL, an application development environment that enables the writing of stored procedures, functions and triggers using both SQL and PL/SQL commands. The course takes the format of a workshop, with a mix of lecture, working examples and practical exercises. Although the content may be customised, at least 2 days are needed to cover the core elements. Full course notes are provided along with sample database files, example SQL files and free software tools for use in accessing an ORACLE database. Introduction Aims and Objectives Course Schedule Introductions Pre-requisites Responsibilities SQL Tools Objectives SQL Developer SQL Developer - Connection Viewing Table Information Using SQL, SQL Developer - Query SQL*Plus Login Direct Connection Using SQL*Plus Ending the Session SQL*Plus Commands SQL*Plus Environment SQL*Plus Prompt Finding Information about Tables Getting Help Using SQL Files iSQL*Plus, Entity Models The ORDERS Tables The FILM Tables Course Tables Handout SQL Statement Syntax SQL*Plus Commands What is PL/SQL? What is PL/SQL? Why Use PL/SQL? Block Structure Displaying a Message Sample Code Setting SERVEROUTPUT Update Example, Style Guide Variables Variables Datatypes Setting Variables Constants Local and Global Variables %Type Variables Substitution Variables Comments with & Verify Option && Variables Define and Undefine SELECT Statement SELECT Statement Populating Variables %Rowtype Variables CHR Function Self Study PL/SQL Records Example Declarations Conditional Statement IF Statement SELECT Statement Self Study Case Statement Trapping Errors Exception Internal Errors Error Code and Message Using No Data Found User Exceptions Raise Application Error Trapping Non-defined Errors Using PRAGMA EXCEPTION_INIT Commit and Rollback Self Study Nested Blocks Workshop Iteration - Looping Loop Statement While Statement For Statement Goto Statement and Labels Cursors Cursors Cursor Attributes Explicit Cursors Explicit Cursor Example Declaring the Cursor Declaring the Variable Open, Fetching the First Row Fetching the Next Row Exit When %Notfound Close For Loop I For Loop II Update Example FOR UPDATE FOR UPDATE OF WHERE CURRENT OF Commit with Cursors Validation Example I Validation Example II Cursor Parameters, Workshop Workshop Solution Procedures, Functions and Packages Create Statement Parameters Procedure Body Showing Errors Describe a Procedure Calling Procedures Calling Procedures in SQL*Plus Using Output Parameters Calling with Output Parameters Creating Functions Example Function Showing Errors Describe a Function Calling Functions Calling Functions in SQL*Plus Modular Programming Example Procedure Calling Functions Calling Functions In An IF Statement Creating Packages Package Example Reasons for Packages Public and Private Sub-programs Showing Errors Describe a Package Calling Packages in SQL*Plus Calling Packages From Sub-Programs Dropping a Sub-Program Finding Sub-programs Creating a Debug Package Calling the Debug Package Positional and Named Notation Parameter Default Values Recompiling Procedures and Functions Workshop Triggers Creating Triggers Statement Triggers Row Level Triggers WHEN Restriction Selective Triggers - IF Showing Errors Commit in Triggers Restrictions Mutating Triggers Finding Triggers Dropping a Trigger Generating an Auto-number Disabling Triggers Enabling Triggers Trigger Names Sample Data ORDER Tables FILM Tables EMPLOYEE Tables Dynamic SQL SQL in PL/SQL Binding Dynamic SQL Native Dynamic SQL DDL and DML DBMS_SQL Package Dynamic SQL - SELECT Dynamic SQL - SELECT Procedure Using Files Using Text Files UTL_FILE Package Write/Append Example Read Example Trigger Example DBMS_ALERT Packages DBMS_JOB Package COLLECTIONS %Type Variables Record Variables Collection Types Index-By Tables Setting Values Nonexistent Elements Nested Tables Nested Table Initialisation Using the Constructor Adding to a Nested Table Varrays Varray Initialization Adding Elements to a Varray Multilevel Collections Bulk Bind Bulk Bind Example Transactional Issues BULK COLLECT Clause RETURNING INTO Ref Cursors Cursor Variables Defining REF CURSOR Types Declaring Cursor Variables Constrained and Unconstrained Using Cursor Variables Cursor Variable Examples
transsqlbas Transact SQL Basic 14小时 Delegates will gain an understanding of the basic principles of Structured Query Language as well as being able to do each of the following: Construct queries to extract and filter data from a SQL Server database Create summarised results Change, derive and format data to suit the required output Change data and maintain database components and definitions This course is for anybody who needs information from a Microsoft SQL Server database. It is suitable for either system developers or people from other areas who need to use SQL to extract and analyse data. Basics Selection of all columns/fields Selection of certain columns/fields Use of distinct/unique Selection of certain rows/records Selection of values in a range Selection of values matching a pattern mask Selection of values within a list Treatment of null values How to sort and order data Selection of calculated and derived values How to control column headings in query results How to send query results to external files Joining Tables Principles of joining tables: Use of cartesian join Use of inner join Use of non-equi join Use of outer join Joining Queries Union operator Intersect operator Except operator Simple Functions Conversion functions Date functions Number functions Text functions Group/summary/aggregate functions Sub-Queries Principles of sub-queries How to filter rows from main query Use of nested sub-query Use of multi-column sub-query Use of correlated sub-query Use of sub-query as an inline view and common table expression Use of sub-query as a column in main query Case Statements Principles of case statements Use of case statement to derive column values Use of nested case statements Use of case statements to produce pivot tables Use of case statement with sub-queries Data Manipulation How to insert values into a table How to copy values between tables How to update values How to delete records How to change data via views Use of transactions How to lock rows and tables Data Definition Principles of a relational database and data normalisation Use of primary key and foreign key relationships and constraints How to create tables How to alter tables How to create views Use of synonyms How to remove tables and views
cassadmin Cassandra Administration 14小时 This course will introduce Cassandra –  a popular NoSQL database.  It will cover Cassandra principles, architecture and data model.   Students will learn data modeling  in CQL (Cassandra Query Language) in hands-on, interactive labs.  This session also discusses Cassandra internals and some admin topics. Section 1: Introduction to Big Data / NoSQL NoSQL overview CAP theorem When is NoSQL appropriate Columnar storage NoSQL ecosystem Section 2 : Cassandra Basics Design and architecture Cassandra nodes, clusters, datacenters Keyspaces, tables, rows and columns Partitioning, replication, tokens Quorum and consistency levels Labs : interacting with cassandra using CQLSH Section 3: Data Modeling – part 1 introduction to CQL CQL Datatypes creating keyspaces & tables Choosing columns and types Choosing primary keys Data layout for rows and columns Time to live (TTL) Querying with CQL CQL updates Collections (list / map / set) Labs : various data modeling exercises using CQL ; experimenting with queries and supported data types Section 4: Data Modeling – part 2 Creating and using secondary indexes composite keys (partition keys and clustering keys) Time series data Best practices for time series data Counters Lightweight transactions (LWT) Labs : creating and using indexes;  modeling time series data Section 5 : Cassandra Internals understand Cassandra design under the hood sstables, memtables, commit log Section 6: Administration Hardware selection Cassandra distributions Cassandra Nodes Communication Writing and Reading data to/from the storage engine Data directories Anti-entropy operations Cassandra Compaction Choosing and Implementing compaction strategies Cassandra best practices (compaction, garbage collection,) troubleshooting tools and tips Lab : students install Cassandra, run benchmarks
ApHadm1 Apache Hadoop: Manipulation and Transformation of Data Performance 21小时 This course is intended for developers, architects, data scientists or any profile that requires access to data either intensively or on a regular basis. The major focus of the course is data manipulation and transformation. Among the tools in the Hadoop ecosystem this course includes the use of Pig and Hive both of which are heavily used for data transformation and manipulation. This training also addresses performance metrics and performance optimisation. The course is entirely hands on and is punctuated by presentations of the theoretical aspects. 1.1Hadoop Concepts 1.1.1HDFS The Design of HDFS Command line interface Hadoop File System 1.1.2Clusters Anatomy of a cluster Mater Node / Slave node Name Node / Data Node 1.2Data Manipulation 1.2.1MapReduce detailed Map phase Reduce phase Shuffle 1.2.2Analytics with Map Reduce Group-By with MapReduce Frequency distributions and sorting with MapReduce Plotting results (GNU Plot) Histograms with MapReduce Scatter plots with MapReduce Parsing complex datasets Counting with MapReduce and Combiners Build reports   1.2.3Data Cleansing Document Cleaning Fuzzy string search Record linkage / data deduplication Transform and sort event dates Validate source reliability Trim Outliers 1.2.4Extracting and Transforming Data Transforming logs Using Apache Pig to filter Using Apache Pig to sort Using Apache Pig to sessionize 1.2.5Advanced Joins Joining data in the Mapper using MapReduce Joining data using Apache Pig replicated join Joining sorted data using Apache Pig merge join Joining skewed data using Apache Pig skewed join Using a map-side join in Apache Hive Using optimized full outer joins in Apache Hive Joining data using an external key value store 1.3Performance Diagnosis and Optimization Techniques Map Investigating spikes in input data Identifying map-side data skew problems Map task throughput Small files Unsplittable files Reduce Too few or too many reducers Reduce-side data skew problems Reduce tasks throughput Slow shuffle and sort Competing jobs and scheduler throttling Stack dumps & unoptimized code Hardware failures CPU contention Tasks Extracting and visualizing task execution times Profiling your map and reduce tasks Avoid the reducer Filter and project Using the combiner Fast sorting with comparators Collecting skewed data Reduce skew mitigation
kdbplusandq kdb+ and q: Analyze time series data 21小时 kdb+ is an in-memory, column-oriented database and q is its built-in, interpreted vector-based language. In kdb+, tables are columns of vectors and q is used to perform operations on the table data as if it was a list. kdb+ and q are commonly used in high frequency trading and are popular with the major financial institutions, including Goldman Sachs, Morgan Stanley, Merrill Lynch, JP Morgan, etc. In this instructor-led, live training, participants will learn how to create a time series data application using kdb+ and q. By the end of this training, participants will be able to: Understand the difference between a row-oriented database and a column-oriented database Select data, write scripts and create functions to carry out advanced analytics Analyze time series data such as stock and commodity exchange data Use kdb+'s in-memory capabilities to store, analyze, process and retrieve large data sets at high speed Think of functions and data at a higher level than the standard function(arguments) approach common in non-vector languages Explore other time-sensitive applications for kdb+, including energy trading, telecommunications, sensor data, log data, and machine and network usage monitoring Audience Developers Database engineers Data scientists Data analysts Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
osqlfun ORACLE SQL Fundamentals 21小时 This 3 day course gives an introduction to SQL Developer, SQL*Plus and to SQL, the Structured Query Language used to access a Relational Database and includes the new features of the latest version of ORACLE. The principles learnt may also be applied to databases as diverse as Microsoft SQL Server, MySQL, Access, Informix and DB2. The course takes the format of a workshop, with a mix of lecture, working examples and practical exercises. Although the content may be customised, at least 2 days are needed to cover the core elements. Full course notes are provided along with sample database files, example SQL files and free software tools for use in accessing an ORACLE database. Introduction Overview Aims and Objectives Sample Data Schedule Introductions Pre-requisites Responsibilities Relational Databases The Database The Relational Database Tables Rows and Columns Sample Database Selecting Rows Supplier Table Saleord Table Primary Key Index Secondary Indexes Relationships Analogy Foreign Key Foreign Key Joining Tables Referential Integrity Types of Relationship Many to Many Relationship Resolving a Many-to-Many Relationship One to One Relationship Completing the Design Resolving Relationships Microsoft Access - Relationships Entity Relationship Diagram Data Modelling CASE Tools Sample Diagram The RDBMS Advantages of an RDBMS Structured Query Language DDL - Data Definition Language DML - Data Manipulation Language DCL - Data Control Language Why Use SQL? Course Tables Handout SQL*Plus SQL*Plus Login Easy Connect Using /NOLOG Using SQL*Plus Ending the Session SQL*Plus Commands SQL*Plus Environment SQL*Plus Prompt LOGIN.SQL File Changing the Password Finding Information about Tables Getting Help Where Clause Using SQL Files iSQL*Plus SQL*Plus Commands Data Retrieval SQL Developer SQL Developer - Connection Viewing Table Information Using SQL, Where Clause Using Comments Character Data Users and Schemas AND and OR Clause Using Brackets Date Fields Using Dates Formatting Dates Date Formats TO_DATE TRUNC Date Display Order By Clause DUAL Table Concatenation Selecting Text IN Operator BETWEEN Operator LIKE Operator Common Errors UPPER Function Single Quotes Finding Metacharacters Regular Expressions REGEXP_LIKE Operator Null Values IS NULL Operator NVL Accepting User Input Data Definition Creating a Table Datatypes Simple Create Example Naming Tables Constraints Not Null Primary Key Foreign Key Check Unique Altering Constraints Full Create Example Data Dictionary Alter Table Secondary Indexes B-tree Index Bitmap Index Create Index Explain Plan Using Indexes Clusters Partitioned Tables Creating a Partitioned Table Rename Drop Statement Flashback Table Managing the Recycle Bin Data Update Insert Some Values Insert All Values Insert Date Values Insert TO_DATE Default Values Using Substitution Variables Transactions Commit Rollback Using Constraints Update Date Arithmetic Update TO_DATE TRUNC Delete Truncate Sequences Grant Create Synonym Create Public Synonym Locking Revoke Savepoint Auto Commit Multi-Table Retrieval Calculations Precedence ROUND Function Column Alias Date Arithmetic Using Aliases CEIL and FLOOR Cartesian Product Table Join Table Alias Selecting the Join Column Joining without Selecting Views Dropping Views Finding Views Derived Columns With Check Option Snapshot Views Flashback Query Using Functions TO_CHAR TO_NUMBER LPAD RPAD NVL NVL2 Function DISTINCT Option SUBSTR INSTR Date Functions Aggregate Functions COUNT Group By Clause Rollup and Cube Modifiers Having Clause Grouping By Functions DECODE CASE Workshop Sub-Query & Union Single Row Sub-queries Union Union - All Intersect and Minus Multiple Row Sub-queries Union – Checking Data Outer Join More On Joins Joins Cross Join or Cartesian Product Inner Join Implicit Join Notation Explicit Join Notation Natural Join Equi-Join Cross Join Outer Joins Left Outer Join Right Outer Join Full Outer Join Using UNION Join Algorithms Nested Loop Merge Join Hash Join Reflexive or Self Join Single Table Join Workshop Advanced Queries ROWNUM and ROWID Top N Analysis Inline View Exists and Not Exists Correlated Sub-queries Correlated Sub-queries with Functions Correlated Update Snapshot Recovery Flashback Recovery All Any and Some Operators Insert ALL Merge Sample Data ORDER Tables FILM Tables EMPLOYEE Tables The ORDER Tables The FILM Tables PL/SQL What is PL/SQL? Why Use PL/SQL? Block Structure Sample Code SELECT Statement Using Variables Accepting User Input Exceptions Other DML Statements Creating Procedures Showing Errors Describe a Procedure Calling Procedures Creating and Running Functions Showing Errors Describe a Function Calling Functions Creating Triggers Showing Errors Query Optimisation Query Optimisation Creating The Tables Timing SQL Statements Other Timing Statements Explain Plan Creating the PLAN_TABLE Table Using SET AUTOTRACE Collecting Statistics Primary Key Secondary Indexes The Query Optimizer Rule Based Optimization Cost Based Optimization Choose Keyword Gathering Statistics Optimizer Hints How to Specify Hints Using Indexes Index Types B*tree Indexes Bitmap Indexes Index-organized table When to Create Indexes Choosing Composite Indexes Using Objects Object-oriented Database Object-relational Database Creating Objects Creating Tables with Objects Using Objects in Tables Large Object Support LOB Datatypes Creating Tables with LOBs Inserting an Empty LOB Creating Tables with BFILEs Creating Directories for BFILEs Inserting a BFILE SQL*PLUS REPORTS Objectives ACCEPT and PROMPT Define and Undefine Creating an SQL*Plus Report Break Command Compute Command Saving the Output in a File Utilities What is a Utility? Export Utility Using Parameters Using a Parameter file Import Utility Using Parameters Using a Parameter file Unloading Data Batch Runs SQL*Loader Utility Running the Utility Appending Data
dnswebmaildb Top 4 Linux/Unix Servers - DNS,Web,Mail and Database 35小时 Created Linux/Unix Administrators and developers who are interested with getting involved in LInux/Unix Servers Even beginners, who have the basic skill and knowledge on Linux, can catch up with this course just if you follow the instructor's lab and explanation in detail. This course is intended to practice enough Managing Linux Servers and to show it is very easy to understand Linux/Unix servers. This course will be delivered to audience with 40% lectures, 50% labs and 10% Q&A. This five-day course strongly emphasizes lab-based activities. You'll learn how to deploy and manage Top 4 Linux Servers that provide highly useful network services to a mission-critical enterprise environment. It can be deliver on any distribution (Fedora, CentOS are commonly used) This course covers these kinds of topics: Bind as a ;DNS server Apache as a Web Server Postfix as a Mail Server MariaDB as a Database Server Through this course, you will learn from the installation to High level features of each server.
dbalogicmigration Database Logic Migration 7小时 When migrating databases there are common ways of dealing with logic put either in SQL queries specific to the database or database procedural language (e.g. PL/SQL). This course covers techniques and strategies of making migration smooth. Also it deals with possible performance and scalability problems. This course is usually deliver with following databases: DB2, Oracle, MySQL, MariaDB, SQL Server, etc... but can be tailored to a specific migration project. Database Logic analysis and problems Where to find logic How to distinguish logic which should be migrated out of database and the logic which can stay Scalability issues Creating unit tests Migration strategies analysis - pros and cons Flexibility vs speed Speed vs scalability Procedural Language to Service PL to PL Removing intermediate derived data (cash) and replacing with life logic OLTP vs Warehouse Design of new logic adapter service Using traditional programming Using Rule Engines or other Logic Engines Unit Testing Performance and scalability issues Changing Client Site ORM (Object-relations mapping) frameworks Using web-service output instead of a query or stored procedure Performance testing Profiling (finding bottlenecks and performing optimisation)
68962 MySQL Administration 32小时 Audience: Any IT professionals who aspire to become DBAs or database support professionals on MySql Database on linx/windows platforms. Format: 40% theoretical/lectures, 60%Practical/hands on lab Introduction MySQL Overview, Products, Services MySQL Services and Support Supported Operating Services Training Curriculum Paths MySQL Documentation Resources MySQL Architecture The client/server model Communication protocols The SQL Layer The Storage Layer How the server supports storage engines How MySQL uses memory and disk space The MySQL plug-in interface System Administration Choosing between types of MySQL distributions Installing the MySQL Server The MySQL Server installation file structure Starting and stopping the MySQL server Upgrading MySQL Running multiple MySQL servers on a single host Server Configuration MySQL server configuration options System variables SQL Modes Available log files Binary logging Clients and Tools Available clients for administrative tasks MySQL administrative clients The mysql command-line client The mysqladmin command-line client The MySQL Workbench graphical client MySQL tools Available APIs (drivers and connectors) Data Types Major categories of data types Meaning of NULL Column attributes Character set usage with data types Choosing an appropriate data type Obtaining Metadata Available metadata access methods Structure of INFORMATION_SCHEMA Using the available commands to view metadata Differences between SHOW statements and INFORMATION_SCHEMA tables The mysqlshow client program Using INFORMATION_SCHEMA queries to create shell commands and SQL statements Transactions and Locking Using transaction control statement to run multiple SQL statements concurrently The ACID properties of transactions Transaction isolation levels Using locking to protect transactions Storage Engines Storage engines in MySQL InnoDB storage engine InnoDB system and file-per-table tablespaces NoSQL and the Memcached API Configuring tablespaces efficiently Using foreign keys to attain referential integrity InnoDB locking Features of available storage engines Partitioning Partitioning and its use in MySQL Reasons for using partitioning Types of partitioning Creating partitioned tables Subpartitioning Obtaining partition metadata Modifying partitions to improve performance Storage Engine Support of Partitioning User Management Requirements for user authentication Using SHOW PROCESSLIST to show which threads are running Creating, modifying and dropping user accounts Alternative authentication plugins Requirements for user authorization Levels of access privileges for users Types of privileges Granting, modifying and revoking user privileges Security Recognizing common security risks Security risks specific to the MySQL installation Security problems and counter-measures for network, operating system, filesystem and users Protecting your data Using SSL for secure MySQL server connections How SSH enables a secure remote connection to the MySQL server Finding additional information for common security issues Table Maintenance Types of table maintenance operations SQL statements for table maintenance Client and utility programs for table maintenance Maintaining tables for other storage engines Exporting and Importing Data Exporting Data Importing Data Programming Inside MySQL Creating and executing Stored Routines Describing stored routine execution security Creating and executing triggers Creating, altering and dropping events Event execution scheduling MySQL Backup and Recovery Backup basics Types of backup Backup tools and utilities Making binary and text backups Role of log and status files in backups Data Recovery Replication Managing the MySQL Binary Log MySQL replication threads and files Setting up a MySQL Replication Environment Designing Complex Replication Topologies Multi-Master and Circular Replication Performing a Controlled Switchover Monitoring and Troubleshooting MySQL Replication Replication with Global Transaction Identifiers (GTIDs) Introduction to Performance Tuning Using EXPLAIN to Analyze Queries General Table Optimizations Monitoring status variables that affect performance Setting and Interpreting MySQL server Variables Overview of Performance Schema Conclusion Q&A Session
riak Riak: Build Applications with High Data Accuracy 14小时 Riak is an Erlang based open-source document database, similar to CouchDB. It is created and maintained by Basho. In this instructor-led, live training, participants will learn how to build, run and operate a Riak based web application. By the end of this training, participants will be able to: Extend the number of hardware nodes and partition data across multiple servers Use bucket/key/values to organize and retrieve documents Use full-text search like query syntax Understand other Riak related technologies, such as Riak KV and Riak TS Test, secure, optimize and deploy a sample web application Audience Developers Database engineers Operations staff Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
mariadbadmin MariaDB Database Administration 14小时 MariaDB Administration training course is for anyone who wants to administrate the MariaDB database server. It is a comprehensive course covering all administrator duties. The course explains how MariaDB Database works, what tools are available, how we can use them, how we can secure the MariaDB Database Server and configure it. During the training course you will learn how to manage user accounts and how the MariaDB Access Privilege System works. You also will learn how to maintain your database, backup and recover your databases and perform crash recovery. Installing MariaDB server Installing in Ubuntu/Debian Installing in other Linux Distributions Installation on Windows MariaDB Server Files and Scripts MariaDB Programs MariaDB Server MariaDB Client GUI Tools MariaDB Server Configuration Server Options The Server SQL Mode Server System Variables Dynamic System Variables Server Status Variables Shutdown Process MariaDB Security Issues Securing MariaDB Against Attacks Security-Related Options Security Issues with LOAD DATA LOCAL MariaDB Access Privilege System MariaDB Privilege System Overview Privileges Provided by MariaDB Connecting to the MariaDB Server - Stages Access Control, Stage 1: Connection Verification Access Control, Stage 2: Request Verification Access Denied Errors MariaDB User Account Management Users and Passwords Creating New Users Deleting User Accounts Limiting User Resources Changing Passwords MariaDB Database Maintenance Backup and Recovery Point-in-Time Recovery Maintenance and Crash Recovery myisamchk Syntax and Options Getting Table Information MariaDB Local Setting National Characters and Sorting MariaDB Server Time Zone MariaDB Log Files Error Log General Query Log Update Log Binary Log Slow Query Log Log File Maintenance and Rotation Running Multiple MariaDB Servers on the Same Machine Running Multiple Servers in Windows Running Multiple Servers in Windows as Services Running Multiple Servers in Unix and Linux Using Client Tools in a Multi-Server Environment MariaDB Query Cache The Concept of Query Cache Testing Query Cache with SELECT Configuring Query Cache Checking Query Cache Status and Maintenance The CONNECT Storage Engine Installing the CONNECT storage engine Creating and dropping CONNECT tables Reading and writing CSV data using CONNECT Reading and writing XML data using CONNECT Accessing MariaDB tables using CONNECT Using the XCOL table type Using the PIVOT table type Using the OCCUR table type Exploring Dynamic and Virtual Columns in MariaDB Creating tables with dynamic columns Inserting, updating, and deleting dynamic column data Reading data from a dynamic column Using virtual columns Performance and Usage Statistics Installing the Audit Plugin Using the Audit Plugin Using engine-independent table statistics Using extended statistics Enabling the performance schema Using the performance schema Optimizing and Tuning MariaDB Using SHOW STATUS Controlling MariaDB optimizer strategies Using extended Keys with InnoDB and XtraDB Configuring the MyISAM segmented key cache Configuring threadpool Configuring the Aria pagecache Optimizing queries with the subquery cache Optimizing semijoin subqueries Using microseconds in DATETIME columns Updating the DATETIME and TIMESTAMP columns automatically  
mariadbdev MariaDB 10 Developer Course 28小时 Created DBAs, Administrators and developers who are interested with getting involved in MariaDB 10 based on Linux system. Even beginners, who have the basic skill and knowledge on Linux, can catch up with this course just if you follow the instructor's lab and explanation in detail. This course is intended to practice enough Database Concept and SQL and to show it is very easy to understand how to use SQL and manage MariaDB on Linux system. This course will be delivered to audience with 40% lectures, 50% labs and 10% Q&A. This five-day course strongly emphasizes lab-based activities After this course, you can apply the knowledge, which you obtained through this course, to the other database systems such as MySQL, Oracle Database, MSSQL Server and PostgreSQL as well. It can be deliver on any distribution (Ubuntu, CentOS are commonly used) This course covers these kinds of topics: Chapter 00 MariaDB 10 Developer Course Introduction Chapter 01 MariaDB 10 Introduction Chapter 02 Startup MariaDB 10 Chapter 03 MariaDB Tools - Command & GUI Chapter 04 Retrieving Data using SQL Chapter 05 Filtering Data using SQL Chapter 06 Summarizing, Grouping & Combining Chapter 07 Database, Table & Indexes Chapter 08 Inserting, Updating & Deleting Data Chapter 09 Table Joins Chapter 10 Subqueries Chapter 11 Views Chapter 12 Stored Procedures Chapter 13 Triggers Chapter 14 MariaDB Datatypes Chapter 15 Transaction Processing Chapter 16 MariaDB User Management Chapter 17 MariaDB Client Tools
datapyth Data Analysis in Python using Pandas and Numpy 14小时 Day 1 Data Analysis with pandas Using vectorized data in pandas Data wrangling Sorting and filtering data Aggregate operations Analyzing time series Data visualisation Plotting diagrams with matplotlib Using matplotlib from within pandas Creating quality diagrams Visualizing data in Jupyter notebooks Other visualization libraries in Python   Day 2 Vectorizing Data in Numpy Creating Numpy arrays Common operations on matrices Using ufuncs Views and broadcasting on Numpy arrays Optimizing performance by avoiding loops Optimizing performance with cProfile Other Python libraries for data analysis scikit-learn Scipy statsmodel RPy2
meanangular2 Angular 2: Building Web Apps using the MEAN stack 35小时 MEAN stack is a full-stack JavaScript solution that helps you write and deploy scalable, robust, and maintainable web applications quickly and easily using MongoDB, Express, Angular, and Node.js. By the end of this hands-on intensive training course, the students will be able to: Store the data in NoSQL, document-oriented MongoDB database that brings performance and scalability. Use Node.js, the server-side platform built on Google V8’s runtime for building fast, scalable network applications. Use Express, a simple yet powerful web application development HTTP server framework built on top of Node.js. Use Angular 2 framework that offers declarative, two-way data binding for web applications. Take advantage of the ‘full-stack JavaScript’ paradigm i.e. store documents in JSON-like format in MongoDB, author JSON queries in Node.js/Express.js, and forward these JSON documents back to an Angular-based frontend. Get acquainted with the latest web application development trends in the IT industry. Notes: Angular is available in different versions, for example: AngularJS ( a.k.a. Angular.js, AngularJS 1, and Angular 1) Angular 2 Angular 4 etc. This training covers Angular 2. For all other components (Node.js, Express, MongDB) we cover the latest stable version. If you wish to customize the versions taught in this training, please contact us to arrange.   Node.js Getting started with Node.js Node Package Manager Modules Asynchronous Programming Callbacks Events Streams Web Sockets Angular 2 Overview of Typescript Angular Architecture Modules, Controllers and Scope Views Two-way Binding Built-in and Custom Directives Event Directives Expressions Built-in and Custom Filters Understanding the Digest Loop Forms and Validation Angular 2 Service Types Factories, Providers, Decorators, DI Creating Custom Services Consuming Ajax Web Services via $http and $resource Routing, Redirects, and Promises Express.js MVC Pattern Introduction to Express Routing HTTP Interaction Handling Form Data Handling Query Parameters Cookies and Sessions User Authentication Error Handling Creating and Consuming RESTful Services Using Templates MongoDB Understanding NoSQL MongoDB Finding Documents Update, Insert, and Upsert Indexing Data Modeling Aggregation
hypertable Hypertable: Deploy a BigTable like database 14小时 Hypertable was an open-source software database management system based on the design of Google's Bigtable. In this instructor-led, live training, participants will learn how to set up and manage a Hypertable database system. By the end of this training, participants will be able to: Install, configure and upgrade a Hypertable instance Set up and administer a Hypertable cluster Monitor and optimize the performance of the database Design a Hypertable schema Work with Hypertable's API Troubleshoot operational issues Audience Developers Operations engineers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
mongodbadmin MongoDB for Administrators 14小时 This course covers everything a database administrator needs to know to successfully deploy and maintain MongoDB databases. Diagnosing performance issues, importing and exporting data, and establishing the proper backup and restore routines, overview of the MongoDB CRUD API, the command shell, and the drivers. are also covered. The audience of this course include people who want to: Understand MongoDB from a developer's perspective, including its command shell, query API, and driver tools. Deploy MongoDB in all its configurations - as a single server, with master/slave replication, as a replica set, and as a sharded cluster. Evaluate applications and choose hardware appropriately. Monitor MongoDB instances and integrate with standard monitoring software (Munin, Nagios, etc.) Plan for backups and manage large data imports and exports. Troubleshoot the most common developer issues and failure scenarios. Each delegate will need to perform a series of practical exercises. MongoDB Architectural Overview Origin, design goals, key features Process structure (mongos, mongod, config servers) Directory / file structure Working with the MongoDB Shell Documents and data types CRUD (Inserts, queries, updates, deletes) System commands Single-server Configuration and Deployment Configuration files Data files and allocation Log files Hardware and file-system recommendations Security Built-in authentication Recommendations for secure deployment Monitoring MongoDB mongostat Analyzing memory and IO performance Integration with monitoring tools: Munin / Cacti / Nagios MongoDB's web console Indexing and Query Optimization Managing indexes and MongoDB indexing internals Single / Compound / Geo indexes Identifying sub-optimal queries. Using the query profiler. Introduction to drivers (Java/Python/Ruby/PHP/Perl) How the drivers and shell communicate with MongoDB BSON and the MongoDB Wire Protocol Troubleshooting application connections Intro to Read and Write scalability Replication and Durability Master-slave replication Replica sets Using write concern for durability Handling replication failures Auto-Sharding How sharding works Setting up a MongoDB shard cluster Choosing a shard key Sharding and indexes Sharding and Replica Set Topologies Administering a sharded cluster Shard / Chunk Migration Backup and Restore Plans Filesystem-based strategies mongodump / mongorestore rsync mongoimport / mongoexport
mean1 Building Web Apps using the MEAN stack 35小时 Course Objective: MEAN stack is a full-stack JavaScript solution that helps you write scalable, robust, and maintainable web applications quickly and easily using MongoDB, express, AngularJS, and Node.js. By the end of this hands-on intensive training course, the students will be able to: Store the data in NoSQL, document-oriented MongoDB database that brings performance and scalability. Use Node.js, the server-side platform built on Google V8’s runtime for building fast, scalable network applications. Use Express, a simple yet powerful web application development HTTP server framework built on top of Node.js. Use AngularJS framework that offers declarative, two-way data binding for web applications. Take advantage of the ‘full-stack JavaScript’ paradigm i.e. store documents in JSON-like format in MongoDB, author JSON queries in Node.js/Express.js, and forward these JSON documents back to an Angular-based frontend. Get acquainted with the latest web application development trends in the IT industry. Node.js Getting started with Node.js Node Package Manager Modules Asynchronous Programming Callbacks Events Streams Web Sockets Angular.js Angular Architecture Modules, Controllers and Scope Views Two-way Binding Built-in and Custom Directives Event Directives Expressions Built-in and Custom Filters Understanding the Digest Loop Forms and Validation AngularJS Service Types Factories, Providers, Decorators, DI Creating Custom Services Consuming Ajax Web Services via $http and $resource Routing, Redirects, and Promises Express.js MVC Pattern Introduction to Express Routing HTTP Interaction Handling Form Data Handling Query Parameters Cookies and Sessions User Authentication Error Handling Creating and Consuming RESTful Services Using Templates MongoDB Understanding NoSQL MongoDB Finding Documents Update, Insert, and Upsert Indexing Data Modeling Aggregation
DM7 Getting started with DM7 (达梦7) 21小时 Audience Beginner or intermediate database developers Beginner or intermediate database administrators Programmers Format of the course Heavy emphasis on hands-on practice. Most of the concepts are learned through samples, exercises and hands-on development Introduction to 达梦7 (达梦数据库管理系统) 达梦7 vs SQL Server, MySQL, and Oracle Installing 达梦7 Creating your first 达梦7 database Configuring your 达梦7 database Tables and Views in 达梦7 Working with SQL Programming 达梦7 Administering 达梦7 Backing up and restoring Security Performance monitoring The future of 达梦7
storm Apache Storm 28小时 Apache Storm is a distributed, real-time computation engine used for enabling real-time business intelligence. It does so by enabling applications to reliably process unbounded streams of data (a.k.a. stream processing). "Storm is for real-time processing what Hadoop is for batch processing!" In this instructor-led live training, participants will learn how to install and configure Apache Storm, then develop and deploy an Apache Storm application for processing big data in real-time. Some of the topics included in this training include: Apache Storm in the context of Hadoop Working with unbounded data Continuous computation Real-time analytics Distributed RPC and ETL processing Request this course now! Audience Software and ETL developers Mainframe professionals Data scientists Big data analysts Hadoop professionals Format of the course     Part lecture, part discussion, exercises and heavy hands-on practice Request a customized course outline for this training!
globalsight Globalsight: Automate the localization process 7小时 Globalight is an open-source, Java based application server for automating, streamlining, and managing the localization process. In this instructor-led, live training, participants will learn about Globalsight's architecture and functionality as they install, configure and deploy a demonstration server . By the end of this training, participants will be able to: Undertand the benefits of Globalsight relative to other Translation Management Systems Install Globalsight server and related components Set up Globalsight to work behind a reverse proxy Build and deploy Globalsight to a production environment Troubleshoot and optimize Globalsight Use Globalsight's APIs to integrate it with third party applications, including JBPM, etc. Audience System administrators Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
mongodbdev MongoDB for Developers 14小时 This course covers everything a database developer needs to know to successfully develop applications using MongoDB. Manipulating Documents Query Insert Update Remove Upsert Removing databases, fields and others Document Structure Datatypes References ID Keys Embedded sub-documents Tree structures Tailable Cursor Two Phase Commits Auto-incrementing Sequence field Aggregation  Distinct Aggregation Pipelines Map-reduce Indexes Default _id Single Field Compound Index Multikey Index Geospatial Index Hashed Index Unique Sparse
trafodionadm1 Administering Trafodion 14小时 NewSQL Concepts  Installation 4 Migrating or Loading Data Connecting to the Database Trafodion SQL vs ANSI SQL Command Interface Managing Cluster
neo4j Beyond the relational database: neo4j 21小时 Relational, table-based databases such as Oracle and MySQL have long been the standard for organizing and storing data. However, the growing size and fluidity of data have made it difficult for these traditional systems to efficiently execute highly complex queries on the data. Imagine replacing rows-and-columns-based data storage with object-based data storage, whereby entities (e.g., a person) could be stored as data nodes, then easily queried on the basis of their vast, multi-linear relationship with other nodes. And imagine querying these connections and their associated objects and properties using a compact syntax, up to 20 times lighter than SQL. This is what graph databases, such as neo4j offer. In this hands-on course, we will set up a live project and put into practice the skills to model, manage and access your data. We contrast and compare graph databases with SQL-based databases as well as other NoSQL databases and clarify when and where it makes sense to implement each within your infrastructure. Audience Database administrators (DBAs) Data analysts Developers System Administrators DevOps engineers Business Analysts CTOs CIOs Format of the course Heavy emphasis on hands-on practice. Most of the concepts are learned through samples, exercises and hands-on development.   Getting started with neo4j neo4j vs relational databases neo4j vs other NoSQL databases Using neo4j to solve real world problems Installing neo4j Data modeling with neo4j Mapping white-board diagrams and mind maps to neo4j Working with nodes Creating, changing and deleting nodes Defining node properties Node relationships Creating and deleting relationships Bi-directional relationships Querying your data with Cypher Querying your data based on relationships MATCH, RETURN, WHERE, REMOVE, MERGE, etc. Setting indexes and constraints Working with the REST API REST operations on nodes REST operations on relationships REST operations on indexes and constraints Accessing the core API for application development Working with NET, Java, Javascript, and Python APIs Closing remarks  
kylin Apache Kylin: From classic OLAP to real-time data warehouse 14小时 Apache Kylin is an extreme, distributed analytics engine for big data. In this instructor-led live training, participants will learn how to use Apache Kylin to set up a real-time data warehouse. By the end of this training, participants will be able to: Consume real-time streaming data using Kylin Utilize Apache Kylin's powerful features, including snowflake schema support, a rich SQL interface, spark cubing and subsecond query latency Note We use the latest version of Kylin (as of this writing, Apache Kylin v2.0) Audience Big data engineers Big Data analysts Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
flockdb Flockdb: A simple graph database for social media 7小时 FlockDB is an open source distributed, fault-tolerant graph database for managing wide but shallow network graphs. It was initially used by Twitter to store relationships among users In this instructor-led, live training, participants will learn how to setup and use a FlockDB database to help answer social media questions such as who follows whom, who blocks whom, etc. By the end of this training, participants will be able to: Install and configure FlockDB Understand the uniqute fetures of FlockDB, relative to other graph databases such Neo4j Use FlockDB to maintain a large graph dataset Use FlockDB together with MySQL to provide provide distributed storage capabilities Query, create and update extremely fast graph edges Scale FlockDB horizontally for use in on-line, low-latency, high throughput web environments Audience Developers Database engineers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice To request a customized course outline for this training, please contact us.
osqlbgn Oracle SQL for beginners 21小时 Listeners This training is addressed for people starting to work with the SQL language in Oracle database The course answer for questions: How to build a query? What possibilities have SQL? What is a relational database? What is the structure and SQL commands Relational database models The structure of a relational database Connection types of tables The normalization and denormalization database Relational Operators Download the data Rules for writing SQL queries The syntax for the SELECT Selecting all columns Inquiries from arithmetic operations Aliases columns Literals Concatenation operator Limiting results The WHERE clause Comparison operators LIKE Condition Prerequisite BETWEEN ... AND IS NULL condition Condition IN Boolean operators AND, OR and NOT Many of the conditions in the WHERE clause The order of the operators. DISTINCT clause Sorting Data The ORDER BY clause Sorting by multiple columns or expressions SQL functions The differences between the functions of one and multilines Features text, numeric, date, Explicit and implicit conversion Conversion functions Nesting functions Viewing the performance of the functions - dual table Getting the current date function SYSDATE Handling of NULL values Aggregating data using the grouping Grouping functions How grouping functions treat NULL values Create groups of data - the GROUP BY clause Grouping multiple columns Limiting the function result grouping - the HAVING clause Retrieving data from multiple tables Types of connectors The use NATURAL JOIN Aliases tables Joins in the WHERE clause INNER JOIN Inner join External Merge LEFT, RIGHT, FULL OUTER JOIN Cartesian product Subqueries Place subqueries in the SELECT command Subqueries single and multi-lineage Operators Subqueries single-line Features grouping in subquery Operators Subqueries multi-IN, ALL, ANY How NULL values ​​are treated in subqueries Operators collective UNION operator UNION ALL operator INTERSECT operator MINUS operator Insert, update, and delete data INSERT command Copy data from another table UPDATE command DELETE command TRUNCATE command Transactions Commands COMMIT, ROLLBACK, and SAVEPOINT DDL commands The main database objects Rules for naming objects Creating tables The data types available for columns DEFAULT option Option NULL and NOT NULL Managing tables Referential integrity CHECK, PRIMARY KEY, FOREIGN KEY, UNIQUE Create a table by the query Delete a table DROP TABLE DESCRIBE command Other schema objects Sequences Synonyms Views
osqladv Oracle SQL Advanced 14小时 Listeners This course is designed for people who want to use the advanced features of SQL in Oracle The course answers the questions How to build advanced queries? How to create advanced reports? Control user access User Management System permissions and object Granting Receiving permission Roles Using the links Managing schema objects ALTER TABLE command Adding, modifying, and deleting columns Add, remove, turn off constraintów Create indexes Flashback operations External tables Operations on large data sets MERGE command DML operations of podzapytaniami DML operations with RETURNING clause INSERT command multi tables Conditional expressions CASE expression DECODE expression Generate reports by grouping related data The GROUP BY clause The HAVING clause Aggregating data - ROLLUP and CUBE operators Identification summaries - GROUPING function Aggregating data - GROUPING SETS operator Managing data in different time zones Time zones Variations TIMESTAMP Differences between DATE and TIMESTAMP Conversion operations Advanced subqueries Subqueries Multi-column subqueries The subquery in the FROM clause Correlated subqueries WITH clause - re-use query blocks Join tables Inequality in the WHERE clause and the FROM clause Semijoin Antijoin The processing of hierarchical data The tree structure hierarchical Queries Pseudo column Sort data in a hierarchical query Useful functions Regular expressions Simple and complex patterns

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