大数据培训

由讲师进行实时指导的大数据本地培训课程将首先介绍大数据的元素概念，然后介绍用于执行数据分析的编程语言和方法。在课程的演示练习环节，我们会讨论、比较并使用用于实现大数据存储、分布式处理、可伸缩性的工具和基础架构。大数据培训形式包括“现场实时培训”和“远程实时培训”。现场实时培训可在客户位于China的所在场所或NobleProg位于China的企业培训中心进行，远程实时培训可通过交互式远程桌面进行。 NobleProg -- 您的本地培训提供商

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其他课程类别

Apache Drill

Apache Spark

Apache ZooKeeper

Dremio

Graph Computing

PySpark

RDF

课程简介

代码	名字	时长	概览
smtwebint	Semantic Web Overview	7小时	The Semantic Web is a collaborative movement led by the World Wide Web Consortium (W3C) that promotes common formats for data on the World Wide Web. The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries.
hadoopdeva	Advanced Hadoop for Developers	21小时	Apache Hadoop is one of the most popular frameworks for processing Big Data on clusters of servers. This course delves into data management in HDFS, advanced Pig, Hive, and HBase. These advanced programming techniques will be beneficial to experienced Hadoop developers. Audience: developers Duration: three days Format: lectures (50%) and hands-on labs (50%).
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.
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
nifidev	Apache NiFi for Developers	7小时	Apache NiFi (Hortonworks DataFlow) is a real-time integrated data logistics and simple event processing platform that enables the moving, tracking and automation of data between systems. It is written using flow-based programming and provides a web-based user interface to manage dataflows in real time. In this instructor-led, live training, participants will learn the fundamentals of flow-based programming as they develop a number of demo extensions, components and processors using Apache NiFi. By the end of this training, participants will be able to: Understand NiFi's architecture and dataflow concepts Develop extensions using NiFi and third-party APIs Custom develop their own Apache Nifi processor Ingest and process real-time data from disparate and uncommon file formats and data sources Audience Developers Data engineers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
mdlmrah	Model MapReduce and Apache Hadoop	14小时	The course is intended for IT specialist that works with the distributed processing of large data sets across clusters of computers.
hadoopdev	Hadoop for Developers (4 days)	28小时	Apache Hadoop is the most popular framework for processing Big Data on clusters of servers. This course will introduce a developer to various components (HDFS, MapReduce, Pig, Hive and HBase) Hadoop ecosystem.
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.
magellan	Magellan: Geospatial Analytics on Spark	14小时	Magellan is an open-source distributed execution engine for geospatial analytics on big data. Implemented on top of Apache Spark, it extends Spark SQL and provides a relational abstraction for geospatial analytics. This instructor-led, live training introduces the concepts and approaches for implementing geospacial analytics and walks participants through the creation of a predictive analysis application using Magellan on Spark. By the end of this training, participants will be able to: Efficiently query, parse and join geospatial datasets at scale Implement geospatial data in business intelligence and predictive analytics applications Use spatial context to extend the capabilities of mobile devices, sensors, logs, and wearables Audience Application developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
matlabpredanalytics	Matlab：用于预测性分析（Predictive Analytics）	21小时	预测性分析是使用数据分析来预测未来的过程。此过程使用数据以及数据挖掘、统计和机器学习技术创建可用来预测未来事件的预测模型。在这一由讲师引导的现场培训中，参与者将学习如何使用Matlab建立预测模型，并将其应用于大样本数据集，以根据数据预测未来事件。在培训结束后，参与者将能够：创建预测模型来分析历史和交易数据中的规律使用预测建模来识别风险和机会建立捕捉重要趋势的数学模型使用来自设备和业务系统的数据来减少浪费、节省时间或降低成本受众开发人员工程师领域专家课程形式部分讲座、部分讨论、练习和大量实操
rneuralnet	Neural Network in R	14小时	This course is an introduction to applying neural networks in real world problems using R-project software.
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. Audience : Developers
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
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
graphcomputing	Introduction to Graph Computing	28小时	A large number of real world problems can be described in terms of graphs. For example, the Web graph, the social network graph, the train network graph and the language graph. These graphs tend to be extremely large; processing them requires a specialized set of tools and processes -- these tools and processes can be referred to as Graph Computing (also known as Graph Analytics). In this instructor-led, live training, participants will learn about the technology offerings and implementation approaches for processing graph data. The aim is to identify real-world objects, their characteristics and relationships, then model these relationships and process them as data using a graph computing approach. We start with a broad overview and narrow in on specific tools as we step through a series of case studies, hands-on exercises and live deployments. By the end of this training, participants will be able to: Understand how graph data is persisted and traversed Select the best framework for a given task (from graph databases to batch processing frameworks) Implement Hadoop, Spark, GraphX and Pregel to carry out graph computing across many machines in parallel View real-world big data problems in terms of graphs, processes and traversals Audience Developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
bdbiga	Big Data Business Intelligence for Govt. Agencies	35小时	Advances in technologies and the increasing amount of information are transforming how business is conducted in many industries, including government. Government data generation and digital archiving rates are on the rise due to the rapid growth of mobile devices and applications, smart sensors and devices, cloud computing solutions, and citizen-facing portals. As digital information expands and becomes more complex, information management, processing, storage, security, and disposition become more complex as well. New capture, search, discovery, and analysis tools are helping organizations gain insights from their unstructured data. The government market is at a tipping point, realizing that information is a strategic asset, and government needs to protect, leverage, and analyze both structured and unstructured information to better serve and meet mission requirements. As government leaders strive to evolve data-driven organizations to successfully accomplish mission, they are laying the groundwork to correlate dependencies across events, people, processes, and information. High-value government solutions will be created from a mashup of the most disruptive technologies: Mobile devices and applications Cloud services Social business technologies and networking Big Data and analytics IDC predicts that by 2020, the IT industry will reach $5 trillion, approximately $1.7 trillion larger than today, and that 80% of the industry's growth will be driven by these 3rd Platform technologies. In the long term, these technologies will be key tools for dealing with the complexity of increased digital information. Big Data is one of the intelligent industry solutions and allows government to make better decisions by taking action based on patterns revealed by analyzing large volumes of data — related and unrelated, structured and unstructured. But accomplishing these feats takes far more than simply accumulating massive quantities of data.“Making sense of thesevolumes of Big Datarequires cutting-edge tools and technologies that can analyze and extract useful knowledge from vast and diverse streams of information,” Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy wrote in a post on the OSTP Blog. The White House took a step toward helping agencies find these technologies when it established the National Big Data Research and Development Initiative in 2012. The initiative included more than $200 million to make the most of the explosion of Big Data and the tools needed to analyze it. The challenges that Big Data poses are nearly as daunting as its promise is encouraging. Storing data efficiently is one of these challenges. As always, budgets are tight, so agencies must minimize the per-megabyte price of storage and keep the data within easy access so that users can get it when they want it and how they need it. Backing up massive quantities of data heightens the challenge. Analyzing the data effectively is another major challenge. Many agencies employ commercial tools that enable them to sift through the mountains of data, spotting trends that can help them operate more efficiently. (A recent study by MeriTalk found that federal IT executives think Big Data could help agencies save more than $500 billion while also fulfilling mission objectives.). Custom-developed Big Data tools also are allowing agencies to address the need to analyze their data. For example, the Oak Ridge National Laboratory’s Computational Data Analytics Group has made its Piranha data analytics system available to other agencies. The system has helped medical researchers find a link that can alert doctors to aortic aneurysms before they strike. It’s also used for more mundane tasks, such as sifting through résumés to connect job candidates with hiring managers.
hadoopba	Hadoop for Business Analysts	21小时	Apache Hadoop is the most popular framework for processing Big Data. Hadoop provides rich and deep analytics capability, and it is making in-roads in to tradional BI analytics world. This course will introduce an analyst to the core components of Hadoop eco system and its analytics Audience Business Analysts Duration three days Format Lectures and hands on labs.
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
samza	Samza for Stream Processing	14小时	Apache Samza is an open-source near-realtime, asynchronous computational framework for stream processing. It uses Apache Kafka for messaging, and Apache Hadoop YARN for fault tolerance, processor isolation, security, and resource management. This instructor-led, live training introduces the principles behind messaging systems and distributed stream processing, while walking participants through the creation of a sample Samza-based project and job execution. By the end of this training, participants will be able to: Use Samza to simplify the code needed to produce and consume messages Decouple the handling of messages from an application Use Samza to implement near-realtime asynchronous computation Use stream processing to provide a higher level of abstraction over messaging systems Audience Developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
bigdatabicriminal	Big Data Business Intelligence for Criminal Intelligence Analysis	35小时	Advances in technologies and the increasing amount of information are transforming how law enforcement is conducted. The challenges that Big Data pose are nearly as daunting as Big Data's promise. Storing data efficiently is one of these challenges; effectively analyzing it is another. In this instructor-led, live training, participants will learn the mindset with which to approach Big Data technologies, assess their impact on existing processes and policies, and implement these technologies for the purpose of identifying criminal activity and preventing crime. Case studies from law enforcement organizations around the world will be examined to gain insights on their adoption approaches, challenges and results. By the end of this training, participants will be able to: Combine Big Data technology with traditional data gathering processes to piece together a story during an investigation Implement industrial big data storage and processing solutions for data analysis Prepare a proposal for the adoption of the most adequate tools and processes for enabling a data-driven approach to criminal investigation Audience Law Enforcement specialists with a technical background Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
iotemi	IoT (Internet of Things) for Entrepreneurs, Managers and Investors	21小时	Unlike other technologies, IoT is far more complex encompassing almost every branch of core Engineering-Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics and Mobile. For each of its engineering layers, there are aspects of economics, standards, regulations and evolving state of the art. This is for the firs time, a modest course is offered to cover all of these critical aspects of IoT Engineering. Summary An advanced training program covering the current state of the art in Internet of Things Cuts across multiple technology domains to develop awareness of an IoT system and its components and how it can help businesses and organizations. Live demo of model IoT applications to showcase practical IoT deployments across different industry domains, such as Industrial IoT, Smart Cities, Retail, Travel & Transportation and use cases around connected devices & things Target Audience Managers responsible for business and operational processes within their respective organizations and want to know how to harness IoT to make their systems and processes more efficient. Entrepreneurs and Investors who are looking to build new ventures and want to develop a better understanding of the IoT technology landscape to see how they can leverage it in an effective manner. Estimates for Internet of Things or IoT market value are massive, since by definition the IoT is an integrated and diffused layer of devices, sensors, and computing power that overlays entire consumer, business-to-business, and government industries. The IoT will account for an increasingly huge number of connections: 1.9 billion devices today, and 9 billion by 2018. That year, it will be roughly equal to the number of smartphones, smart TVs, tablets, wearable computers, and PCs combined. In the consumer space, many products and services have already crossed over into the IoT, including kitchen and home appliances, parking, RFID, lighting and heating products, and a number of applications in Industrial Internet. However, the underlying technologies of IoT are nothing new as M2M communication existed since the birth of Internet. However what changed in last couple of years is the emergence of number of inexpensive wireless technologies added by overwhelming adaptation of smart phones and Tablet in every home. Explosive growth of mobile devices led to present demand of IoT. Due to unbounded opportunities in IoT business, a large number of small and medium sized entrepreneurs jumped on a bandwagon of IoT gold rush. Also due to emergence of open source electronics and IoT platform, cost of development of IoT system and further managing its sizable production is increasingly affordable. Existing electronic product owners are experiencing pressure to integrate their device with Internet or Mobile app. This training is intended for a technology and business review of an emerging industry so that IoT enthusiasts/entrepreneurs can grasp the basics of IoT technology and business. Course Objective Main objective of the course is to introduce emerging technological options, platforms and case studies of IoT implementation in home & city automation (smart homes and cities), Industrial Internet, healthcare, Govt., Mobile Cellular and other areas. Basic introduction of all the elements of IoT-Mechanical, Electronics/sensor platform, Wireless and wireline protocols, Mobile to Electronics integration, Mobile to enterprise integration, Data-analytics and Total control plane M2M Wireless protocols for IoT- WiFi, Zigbee/Zwave, Bluetooth, ANT+ : When and where to use which one? Mobile/Desktop/Web app- for registration, data acquisition and control –Available M2M data acquisition platform for IoT-–Xively, Omega and NovoTech, etc. Security issues and security solutions for IoT Open source/commercial electronics platform for IoT-Raspberry Pi, Arduino , ArmMbedLPC etc Open source /commercial enterprise cloud platform for AWS-IoT apps, Azure -IOT, Watson-IOT cloud in addition to other minor IoT clouds Studies of business and technology of some of the common IoT devices like Home automation, Smoke alarm, vehicles, military, home health etc.
dataar	Data Analytics With R	21小时	R is a very popular, open source environment for statistical computing, data analytics and graphics. This course introduces R programming language to students. It covers language fundamentals, libraries and advanced concepts. Advanced data analytics and graphing with real world data. Audience Developers / data analytics Duration 3 days Format Lectures and Hands-on
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
flink	Flink for Scalable Stream and Batch Data Processing	28小时	Apache Flink is an open-source framework for scalable stream and batch data processing. This instructor-led, live training introduces the principles and approaches behind distributed stream and batch data processing, and walks participants through the creation of a real-time, data streaming application. By the end of this training, participants will be able to: Set up an environment for developing data analysis applications Package, execute, and monitor Flink-based, fault-tolerant, data streaming applications Manage diverse workloads Perform advanced analytics using Flink ML Set up a multi-node Flink cluster Measure and optimize performance Integrate Flink with different Big Data systems Compare Flink capabilities with those of other big data processing frameworks Audience Developers Architects Data engineers Analytics professionals Technical managers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
sparkpython	用Spark和Python通过PySpark处理大数据	21小时	Spark是一个用于查询、分析和转换大数据的数据处理引擎。Python是一种高级编程语言，因其清晰的语法和代码可读性而闻名。PySpark允许用户将Spark与Python连接。在这一由讲师引导的现场培训中，学员将通过实践练习学习如何使用Python和Spark一起分析大数据。在本次培训结束后，学员将能够：了解如何使用Spark和Python一起分析大数据开展模拟真实世界环境的练习用不同的工具和技术通过PySpark进行大数据分析受众开发人员 IT专业人士数据科学家课程形式部分讲座、部分讨论、练习和大量实操
bdbitcsp	为电信服务供应商的智能大数据信息业务	35小时	Overview Communications service providers (CSP) are facing pressure to reduce costs and maximize average revenue per user (ARPU), while ensuring an excellent customer experience, but data volumes keep growing. Global mobile data traffic will grow at a compound annual growth rate (CAGR) of 78 percent to 2016, reaching 10.8 exabytes per month. Meanwhile, CSPs are generating large volumes of data, including call detail records (CDR), network data and customer data. Companies that fully exploit this data gain a competitive edge. According to a recent survey by The Economist Intelligence Unit, companies that use data-directed decision-making enjoy a 5-6% boost in productivity. Yet 53% of companies leverage only half of their valuable data, and one-fourth of respondents noted that vast quantities of useful data go untapped. The data volumes are so high that manual analysis is impossible, and most legacy software systems can’t keep up, resulting in valuable data being discarded or ignored. With Big Data & Analytics’ high-speed, scalable big data software, CSPs can mine all their data for better decision making in less time. Different Big Data products and techniques provide an end-to-end software platform for collecting, preparing, analyzing and presenting insights from big data. Application areas include network performance monitoring, fraud detection, customer churn detection and credit risk analysis. Big Data & Analytics products scale to handle terabytes of data but implementation of such tools need new kind of cloud based database system like Hadoop or massive scale parallel computing processor ( KPU etc.) This course work on Big Data BI for Telco covers all the emerging new areas in which CSPs are investing for productivity gain and opening up new business revenue stream. The course will provide a complete 360 degree over view of Big Data BI in Telco so that decision makers and managers can have a very wide and comprehensive overview of possibilities of Big Data BI in Telco for productivity and revenue gain. Course objectives Main objective of the course is to introduce new Big Data business intelligence techniques in 4 sectors of Telecom Business (Marketing/Sales, Network Operation, Financial operation and Customer Relation Management). Students will be introduced to following: Introduction to Big Data-what is 4Vs (volume, velocity, variety and veracity) in Big Data- Generation, extraction and management from Telco perspective How Big Data analytic differs from legacy data analytic In-house justification of Big Data -Telco perspective Introduction to Hadoop Ecosystem- familiarity with all Hadoop tools like Hive, Pig, SPARC –when and how they are used to solve Big Data problem How Big Data is extracted to analyze for analytics tool-how Business Analysis’s can reduce their pain points of collection and analysis of data through integrated Hadoop dashboard approach Basic introduction of Insight analytics, visualization analytics and predictive analytics for Telco Customer Churn analytic and Big Data-how Big Data analytic can reduce customer churn and customer dissatisfaction in Telco-case studies Network failure and service failure analytics from Network meta-data and IPDR Financial analysis-fraud, wastage and ROI estimation from sales and operational data Customer acquisition problem-Target marketing, customer segmentation and cross-sale from sales data Introduction and summary of all Big Data analytic products and where they fit into Telco analytic space Conclusion-how to take step-by-step approach to introduce Big Data Business Intelligence in your organization Target Audience Network operation, Financial Managers, CRM managers and top IT managers in Telco CIO office. Business Analysts in Telco CFO office managers/analysts Operational managers QA managers
hadoopadm1	Hadoop For Administrators	21小时	Apache Hadoop is the most popular framework for processing Big Data on clusters of servers. In this three (optionally, four) days course, attendees will learn about the business benefits and use cases for Hadoop and its ecosystem, how to plan cluster deployment and growth, how to install, maintain, monitor, troubleshoot and optimize Hadoop. They will also practice cluster bulk data load, get familiar with various Hadoop distributions, and practice installing and managing Hadoop ecosystem tools. The course finishes off with discussion of securing cluster with Kerberos. “…The materials were very well prepared and covered thoroughly. The Lab was very helpful and well organized” — Andrew Nguyen, Principal Integration DW Engineer, Microsoft Online Advertising Audience Hadoop administrators Format Lectures and hands-on labs, approximate balance 60% lectures, 40% labs.
BigData_	数据分析和大数据的实用介绍	35小时	参与者完成此次培训后，将会对大数据及其相关技术、方法、工具有一个实际和真实的理解。参与者将有机会通过动手练习将这些知识付诸实践。小组互动和讲师反馈是课堂的重要组成部分。本课程首先介绍大数据的基本概念，然后讲解用于执行数据分析的编程语言和方法，最后我们会讨论可启用大数据存储、分布式处理及可扩展性的工具和基础架构。受众开发人员/程序员 IT顾问课程形式部分讲座、部分讨论、实操、偶尔测评进度
alluxio	Alluxio: Unifying disparate storage systems	7小时	Alexio is an open-source virtual distributed storage system that unifies disparate storage systems and enables applications to interact with data at memory speed. It is used by companies such as Intel, Baidu and Alibaba. In this instructor-led, live training, participants will learn how to use Alexio to bridge different computation frameworks with storage systems and efficiently manage multi-petabyte scale data as they step through the creation of an application with Alluxio. By the end of this training, participants will be able to: Develop an application with Alluxio Connect big data systems and applications while preserving one namespace Efficiently extract value from big data in any storage format Improve workload performance Deploy and manage Alluxio standalone or clustered Audience Data scientist Developer System administrator Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
apachedrill	Apache Drill用于飞速分析多种大数据格式	21小时	Apache Drill是一种无模式、分布式、内存列式SQL查询引擎，用于Hadoop、NoSQL及其他云和文件存储系统。Apache Drill的强大之处在于它能够使用单个查询连接来自多个数据存储的数据。Apache Drill支持许多NoSQL数据库和文件系统，包括HBase、MongoDB、MapR-DB、HDFS、MapR-FS、Amazon S3、Azure Blob Storage、Google Cloud Storage、Swift、NAS和本地文件。在这一由讲师引导的现场培训中，学员将学习Apache Drill的基础知识，然后利用SQL的强大功能和便利性在无需编写代码的情况下交互式查询大数据。学员还将学习如何优化分布式SQL执行的Drill查询。在本次培训结束后，学员将能够：对Hadoop上的结构化和半结构化数据进行“自助式”探索使用SQL查询来查询已知以及未知数据了解Apache Drills如何接收和执行查询编写SQL查询来分析不同类型的数据，包括Hive中的结构化数据，HBase或MapR-DB表中的半结构化数据，以及Parquet和JSON文件中保存的数据。使用Apache Drill执行即时模式发现，绕过对复杂ETL和模式操作的需求将Apache Drill与BI（商业智能）工具（如Tableau、Qlikview、MicroStrategy、Excel）集成在一起受众数据分析师数据科学家 SQL程序员课程形式部分讲座、部分讨论、练习和大量实操
apacheh	Administrator Training for Apache Hadoop	35小时	Audience: The course is intended for IT specialists looking for a solution to store and process large data sets in a distributed system environment Goal: Deep knowledge on Hadoop cluster administration.
solrdev	Solr for Developers	21小时	This course introduces students to the Solr platform. Through a combination of lecture, discussion and labs students will gain hands on experience configuring effective search and indexing. The class begins with basic Solr installation and configuration then teaches the attendees the search features of Solr. Students will gain experience with faceting, indexing and search relevance among other features central to the Solr platform. The course wraps up with a number of advanced topics including spell checking, suggestions, Multicore and SolrCloud. Duration: 3 days Audience: Developers, business users, administrators
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
apex	Apache Apex: Processing big data-in-motion	21小时	Apache Apex is a YARN-native platform that unifies stream and batch processing. It processes big data-in-motion in a way that is scalable, performant, fault-tolerant, stateful, secure, distributed, and easily operable. This instructor-led, live training introduces Apache Apex's unified stream processing architecture and walks participants through the creation of a distributed application using Apex on Hadoop. By the end of this training, participants will be able to: Understand data processing pipeline concepts such as connectors for sources and sinks, common data transformations, etc. Build, scale and optimize an Apex application Process real-time data streams reliably and with minimum latency Use Apex Core and the Apex Malhar library to enable rapid application development Use the Apex API to write and re-use existing Java code Integrate Apex into other applications as a processing engine Tune, test and scale Apex applications Audience Developers Enterprise architects Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
aifortelecom	AI Awareness for Telecom	14小时	AI is a collection of technologies for building intelligent systems capable of understanding data and the activities surrounding the data to make "intelligent decisions". For Telecom providers, building applications and services that make use of AI could open the door for improved operations and servicing in areas such as maintenance and network optimization. In this course we examine the various technologies that make up AI and the skill sets required to put them to use. Throughout the course, we examine AI's specific applications within the Telecom industry. Audience Network engineers Network operations personnel Telecom technical managers Format of the course Part lecture, part discussion, hands-on exercises
hadoopadm	Hadoop Administration	21小时	The course is dedicated to IT specialists that are looking for a solution to store and process large data sets in distributed system environment Course goal: Getting knowledge regarding Hadoop cluster administration
sparkdev	Spark for Developers	21小时	OBJECTIVE: This course will introduce Apache Spark. The students will learn how Spark fits into the Big Data ecosystem, and how to use Spark for data analysis. The course covers Spark shell for interactive data analysis, Spark internals, Spark APIs, Spark SQL, Spark streaming, and machine learning and graphX. AUDIENCE : Developers / Data Analysts
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.
vespa	Vespa: Serving large-scale data in real-time	14小时	Vespa an open-source big data processing and serving engine created by Yahoo. It is used to respond to user queries, make recommendations, and provide personalized content and advertisements in real-time. This instructor-led, live training introduces the challenges of serving large-scale data and walks participants through the creation of an application that can compute responses to user requests, over large datasets in real-time. By the end of this training, participants will be able to: Use Vespa to quickly compute data (store, search, rank, organize) at serving time while a user waits Implement Vespa into existing applications involving feature search, recommendations, and personalization Integrate and deploy Vespa with existing big data systems such as Hadoop and Storm. Audience Developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
apachedrillqueryoptim	Apache Drill Query Optimization	7小时	Apache Drill is a schema-free, distributed, in-memory columnar SQL query engine for Hadoop, NoSQL and other Cloud and file storage systems. The power of Apache Drill lies in its ability to join data from multiple data stores using a single query. Apache Drill supports numerous NoSQL databases and file systems, including HBase, MongoDB, MapR-DB, HDFS, MapR-FS, Amazon S3, Azure Blob Storage, Google Cloud Storage, Swift, NAS and local files. Apache Drill is the open source version of Google's Dremel system which is available as an infrastructure service called Google BigQuery. In this instructor-led, live training, participants will learn how to optimize and debug Apache Drill to improve the performance of queries on very large data sets. The course begins with an architectural overview and feature comparison between Apache Drill and other interactive data analysis tools. Participants then step through a series of interactive, hands-on practice sessions that include installation, configuration, performance evaluation, query optimization, data partitioning, and debugging of an Apache Drill instance in a live lab environment. By the end of this training, participants will be able to: Install and configure Apache Drill Understand Apache Drill's architecture and features Understand how Apache Drills receives and executes queries Optimize Drill queries for distributed SQL execution Debug Apache Drill Audience Developers Systems administrators Data analysts Format of the course Part lecture, part discussion, exercises and heavy hands-on practice Notes To request a customized training for this course, please contact us to arrange.
datamin	Data Mining	21小时	Course can be provided with any tools, including free open-source data mining software and applications
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
hadoopforprojectmgrs	面向项目经理的Hadoop	14小时	随着越来越多的软件和IT项目从本地处理和数据管理转向分布式处理和大数据存储，项目经理们正在意识到需要升级他们的知识和技能，以掌握与大数据项目和机会相关的概念和实践。本课程将向项目经理介绍当下最流行的大数据处理框架：Hadoop。在这一由讲师引导的培训中，学员将学习Hadoop生态系统的核心组件，以及这些技术如何用于解决大规模问题。在学习这些基础的过程中，学员还将提高他们与这些系统的开发人员和实施人员以及许多IT项目涉及的数据科学家和分析师沟通的能力。受众希望将Hadoop应用到其现有开发或IT基础架构中的项目经理需要与包括大数据工程师、数据科学家和业务分析师在内的跨职能团队进行沟通的项目经理课程形式部分讲座、部分讨论、练习和大量实操
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
dremio	Dremio for Self-Service Data Analysis	21小时	Dremio is an open-source "self-service data platform" that accelerates the querying of different types of data sources. Dremio integrates with relational databases, Apache Hadoop, MongoDB, Amazon S3, ElasticSearch, and other data sources. It supports SQL and provides a web UI for building queries. In this instructor-led, live training, participants will learn how to install, configure and use Dremio as a unifying layer for data analysis tools and the underlying data repositories. By the end of this training, participants will be able to: Install and configure Dremio Execute queries against multiple data sources, regardless of location, size, or structure Integrate Dremio with BI and data sources such as Tableau and Elasticsearch Audience Data scientists Business analysts Data engineers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice Notes To request a customized training for this course, please contact us to arrange.
d2dbdpa	From Data to Decision with Big Data and Predictive Analytics	21小时	Audience If you try to make sense out of the data you have access to or want to analyse unstructured data available on the net (like Twitter, Linked in, etc...) this course is for you. It is mostly aimed at decision makers and people who need to choose what data is worth collecting and what is worth analyzing. It is not aimed at people configuring the solution, those people will benefit from the big picture though. Delivery Mode During the course delegates will be presented with working examples of mostly open source technologies. Short lectures will be followed by presentation and simple exercises by the participants Content and Software used All software used is updated each time the course is run so we check the newest versions possible. It covers the process from obtaining, formatting, processing and analysing the data, to explain how to automate decision making process with machine learning.
68736	Hadoop for Developers (2 days)	14小时
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
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
bigdataM	Big Data and its Management Process	14小时	Objective : This training course aims at helping attendees understand why Big Data is changing our lives and how it is altering the way businesses see us as consumers. Indeed, users of big data in businesses find that big data unleashes a wealth of information and insights which translate to higher profits, reduced costs, and less risk. However, the downside was frustration sometimes when putting too much emphasis on individual technologies and not enough focus on the pillars of big data management. Attendees will learn during this course how to manage the big data using its three pillars of data integration, data governance and data security in order to turn big data into real business value. Different exercices conducted on a case study of customer management will help attendees to better understand the underlying processes.
apachemdev	Apache Mahout for Developers	14小时	Audience Developers involved in projects that use machine learning with Apache Mahout. Format Hands on introduction to machine learning. The course is delivered in a lab format based on real world practical use cases.
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.
glusterfs	GlusterFS for System Administrators	21小时	GlusterFS is an open-source distributed file storage system that can scale up to petabytes of capacity. GlusterFS is designed to provide additional space depending on the user's storage requirements. A common application for GlusterFS is cloud computing storage systems. In this instructor-led training, participants will learn how to use normal, off-the-shelf hardware to create and deploy a storage system that is scalable and always available. By the end of the course, participants will be able to: Install, configure, and maintain a full-scale GlusterFS system. Implement large-scale storage systems in different types of environments. Audience System administrators Storage administrators Format of the Course Part lecture, part discussion, exercises and heavy hands-on practice.
datavault	Data Vault: Building a Scalable Data Warehouse	28小时	Data vault modeling is a database modeling technique that provides long-term historical storage of data that originates from multiple sources. A data vault stores a single version of the facts, or "all the data, all of the time". Its flexible, scalable, consistent and adaptable design encompasses the best aspects of 3rd normal form (3NF) and star schema. In this instructor-led, live training, participants will learn how to build a Data Vault. By the end of this training, participants will be able to: Understand the architecture and design concepts behind Data Vault 2.0, and its interaction with Big Data, NoSQL and AI. Use data vaulting techniques to enable auditing, tracing, and inspection of historical data in a data warehouse Develop a consistent and repeatable ETL (Extract, Transform, Load) process Build and deploy highly scalable and repeatable warehouses Audience Data modelers Data warehousing specialist Business Intelligence specialists Data engineers Database administrators Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
sparksql	Apache Spark SQL	7小时	Spark SQL is Apache Spark's module for working with structured and unstructured data. Spark SQL provides information about the structure of the data as well as the computation being performed. This information can be used to perform optimizations. Two common uses for Spark SQL are: - to execute SQL queries. - to read data from an existing Hive installation. In this instructor-led, live training (onsite or remote), participants will learn how to analyze various types of data sets using Spark SQL. By the end of this training, participants will be able to: Install and configure Spark SQL. Perform data analysis using Spark SQL. Query data sets in different formats. Visualize data and query results. Audience Data analysts Data scientists Data engineers Format of the Course Part lecture, part discussion, exercises and heavy hands-on practice Notes To request a customized training for this course, please contact us to arrange.
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.
dsbda	Data Science for Big Data Analytics	35小时	Big data is data sets that are so voluminous and complex that traditional data processing application software are inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating and information privacy.
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
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
introtostreamprocessing	A Practical Introduction to Stream Processing	21小时	Stream Processing refers to the real-time processing of "data in motion", that is, performing computations on data as it is being received. Such data is read as continuous streams from data sources such as sensor events, website user activity, financial trades, credit card swipes, click streams, etc. Stream Processing frameworks are able to read large volumes of incoming data and provide valuable insights almost instantaneously. In this instructor-led, live training (onsite or remote), participants will learn how to setup and integrate different Stream Processing frameworks with existing big data storage systems and related software applications and microservices. By the end of this training, participants will be able to: Install and configure different Stream Processing frameworks, such as Spark Streaming and Kafka Streaming Understand and select the most appropriate framework for the job Process of data continuously, concurrently, and in a record-by-record fashion Integrate Stream Processing solutions with existing databases, data warehouses, data lakes, etc. Integrating the most appropriate stream processing library with enterprise applications and microservices Audience Developers Software architects Format of the Course Part lecture, part discussion, exercises and heavy hands-on practice Notes To request a customized training for this course, please contact us to arrange.
bigdatar	Programming with Big Data in R	21小时	Big Data is a term that refers to solutions destined for storing and processing large data sets. Developed by Google initially, these Big Data solutions have evolved and inspired other similar projects, many of which are available as open-source. R is a popular programming language in the financial industry.
zookeeper	Apache Zookeeper	14小时	ZooKeeper is a centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services.
matlabfundamentalsfinance	MATLAB基础 + MATLAB用于财务工作	35小时	本课程提供了MATLAB技术计算环境的全面介绍，及使用MATLAB进行金融应用的介绍。本课程面向初级使用者及有意复习相关知识的使用者。不需有编程经验或MATLAB知识。在整个课程中探讨数据分析、可视化、建模、编程等主题。主题包括：使用MATLAB用户界面输入命令并创建变量分析向量和矩阵可视化矢量和矩阵数据使用数据文件处理数据类型使用脚本自动执行命令用逻辑和流控制编写程序写作功能使用金融工具箱进行定量分析
solrcloud	SolrCloud	14小时	Apache SolrCloud is a distributed data processing engine that facilitates the searching and indexing of files on a distributed network. In this instructor-led, live training, participants will learn how to set up a SolrCloud instance on Amazon AWS. By the end of this training, participants will be able to: Understand SolCloud's features and how they compare to those of conventional master-slave clusters Configure a SolCloud centralized cluster Automate processes such as communicating with shards, adding documents to the shards, etc. Use Zookeeper in conjunction with SolrCloud to further automate processes Use the interface to manage error reporting Load balance a SolrCloud installation Configure SolrCloud for continuous processing and fail-over Audience Solr Developers Project Managers System Administrators Search Analysts Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
beam	Unified Batch and Stream Processing with Apache Beam	14小时	Apache Beam is an open source, unified programming model for defining and executing parallel data processing pipelines. It's power lies in its ability to run both batch and streaming pipelines, with execution being carried out by one of Beam’s supported distributed processing back-ends: Apache Apex, Apache Flink, Apache Spark, and Google Cloud Dataflow. Apache Beam is useful for ETL (Extract, Transform, and Load) tasks such as moving data between different storage media and data sources, transforming data into a more desirable format, and loading data onto a new system. In this instructor-led, live training (onsite or remote), participants will learn how to implement the Apache Beam SDKs in a Java or Python application that defines a data processing pipeline for decomposing a big data set into smaller chunks for independent, parallel processing. By the end of this training, participants will be able to: Install and configure Apache Beam Use a single programming model to carry out both batch and stream processing from withing their Java or Python application Execute pipelines across multiple environments Audience Developers Format of the Course Part lecture, part discussion, exercises and heavy hands-on practice Note This course will be available Scala in the future. Please contact us to arrange.
datashrinkgov	Data Shrinkage for Government	14小时	The objective of the course is to enable participants to gain a mastery of the fundamentals of data shrinkage for government.
IntroToAvro	Apache Avro: Data serialization for distributed applications	14小时	This course is intended for Developers Format of the course Lectures, hands-on practice, small tests along the way to gauge understanding
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 Upload to and extract large records from Hadoop, Hive, and NoSQL databases 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
hypertable	Hypertable: Deploy a BigTable like database	14小时	Hypertable is 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
bigdataanahealth	Big Data Analytics in Health	21小时	Big data analytics involves the process of examining large amounts of varied data sets in order to uncover correlations, hidden patterns, and other useful insights. The health industry has massive amounts of complex heterogeneous medical and clinical data. Applying big data analytics on health data presents huge potential in deriving insights for improving delivery of healthcare. However, the enormity of these datasets poses great challenges in analyses and practical applications to a clinical environment. In this instructor-led, live training (remote), participants will learn how to perform big data analytics in health as they step through a series of hands-on live-lab exercises. By the end of this training, participants will be able to: Install and configure big data analytics tools such as Hadoop MapReduce and Spark Understand the characteristics of medical data Apply big data techniques to deal with medical data Study big data systems and algorithms in the context of health applications Audience Developers Data Scientists Format of the Course Part lecture, part discussion, exercises and heavy hands-on practice. Note To request a customized training for this course, please contact us to arrange.
matlab2	MATLAB 基础	21小时	MATLAB软件简介 MATLAB（矩阵实验室）是MATrix LABoratory的缩写,是一款由美国The MathWorks公司出品的商业科学计算和仿真软件.MATLAB拥有一套可用于算法开发,数据可视化,数据分析以及数值计算的高级技术计算语言和交互式环境.除了矩阵运算,求解线性系统方程,绘制函数/数据图像等常用功能外,MATLAB还可以用来创建用户界面及与调用其它语言（包括C,C++,Java,Python和FORTRAN）编写的程序。尽管MATLAB最初主要用于科学计算,但其不断增加的各种附加工具箱(到目前为止将近100个)使之适合不同领域和行业的应用,如控制系统设计与分析,生物医疗,图像处理,信号处理与通讯,金融建模和分析,汽车,航天航空等。另外还有一个基于模型化设计(MBD)的图形化仿真软件包Simulink用于系统模拟,代码生成,动态/嵌入式系统开发等方面. 培训目的本课程将全面介绍MATLAB科学技术计算环境,旨在于使初学者迅速掌握MATLAB原理,在课程结束后可以: -> 熟悉MATLAB界面,查找帮助; -> 键入命令,进行变量,向量和矩阵的基本操作; -> 对数据进行多种可视化展示; -> 处理数据文件和不同数据类型; -> 编写脚本和函数,并在其中包含必要的逻辑和分支控制; -> 读写文本和二进制文件课程特色本次课程使用MATLAB2014a用于演示。本着由浅入深,注重实践,重点问题反复强调的原则,不拘泥于PPT讲义,尽量多使用实例进行示范操作.
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
pythonmultipurpose	高级Python	28小时	在这一由讲师引导的培训中，参与者将学习高级Python编程技术，包括如何将这种多功能语言应用于解决分布式应用、财务、数据分析和可视化、UI编程及维护脚本等领域的问题。受众开发人员课程形式部分讲座、部分讨论、练习和大量实操注意事项如果您想添加、移除或自定义本课程中的任一部分或主题，请联系我们以作安排。
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 unique features 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
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.
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.
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
nifi	Apache NiFi for Administrators	21小时	Apache NiFi (Hortonworks DataFlow) is a real-time integrated data logistics and simple event processing platform that enables the moving, tracking and automation of data between systems. It is written using flow-based programming and provides a web-based user interface to manage dataflows in real time. In this instructor-led, live training, participants will learn how to deploy and manage Apache NiFi in a live lab environment. By the end of this training, participants will be able to: Install and configure Apachi NiFi Source, transform and manage data from disparate, distributed data sources, including databases and big data lakes Automate dataflows Enable streaming analytics Apply various approaches for data ingestion Transform Big Data and into business insights Audience System administrators Data engineers Developers DevOps Format of the course Part lecture, part discussion, exercises and heavy hands-on practice

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促销课程

课程

地址

日期

价格【远程 / 传统课堂】

Linux LPI LPIC-2 Exam 201 Preparation

深圳 - 新世界中心

星期三, 2018-07-04 09:30

￥16362 / ￥20742

Hadoop Administration

北京盈科中心

星期二, 2018-08-21 09:30

￥25767 / ￥29367

Linux LPI LPIC-2 Exam 202 Preparation

苏州 - 晋合广场

星期四, 2018-08-23 09:30

￥16362 / ￥18762

Applied Machine Learning

北京盈科中心

星期三, 2018-09-26 09:30

￥16092 / ￥18892

Managing Business Logic with Drools

苏州 - 晋合广场

星期一, 2018-11-05 09:30

￥16200 / ￥19200

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