Data Warehouse培训课程

The course is part of the Data Scientist skill set (Domain: Data and Technology).

Apache 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 instructor-led, live 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.

Format of the Course

- Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding

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, 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

MemSQL is an in-memory, distributed, SQL database management system for cloud and on-premises. It's a real-time data warehouse that immediately delivers insights from live and historical data.

In this instructor-led, live training, participants will learn the essentials of MemSQL for development and administration.

By the end of this training, participants will be able to:

- Understand the key concepts and characteristics of MemSQL
- Install, design, maintain, and operate MemSQL
- Optimize schemas in MemSQL
- Improve queries in MemSQL
- Benchmark performance in MemSQL
- Build real-time data applications using MemSQL

Audience

- Developers
- Administrators
- Operation Engineers

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice

Amazon Redshift is a petabyte-scale cloud-based data warehouse service in AWS.

In this instructor-led, live training, participants will learn the fundamentals of Amazon Redshift.

By the end of this training, participants will be able to:

- Install and configure Amazon Redshift
- Load, configure, deploy, query, and visualize data with Amazon Redshift

Audience

- Developers
- IT Professionals

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.

This instructor-led, live training in 中国 (online or onsite) is aimed at developers who wish to set up a multi-node Greenplum database.

By the end of this training, participants will be able to:

- Install and configure Pivotal Greenplum.
- Model data in accordance to current needs and future expansion plans.
- Carry out different techniques for distribute data across multiple nodes.
- Improve database performance through tuning.
- Monitor and troubleshoot a Greenplum database.

This instructor-led, live training in 中国 (online or onsite) is aimed at administrators who wish to set up Greenplum Database for business intelligence and data warehousing solutions.

By the end of this training, participants will be able to:

- Address processing needs with Greenplum.
- Perform ETL operations for data processing.
- Leverage existing query processing infrastructures.

Data Vault建模是一种数据库建模技术，可提供源自多个源的数据的长期历史存储。一个Data Vault存储事实或“所有数据、所有时间”的单个版本。其灵活、可扩展、一致且适应性强的设计涵盖了第三范式（3NF）和星型模型（star schema）的最佳方面。

在这一由讲师指导的实时培训中，学员将学习如何构建一个Data Vault。

在本次培训结束之后，学员将能够：

- 了解Data Vault 2.0背后的架构和设计概念，以及它与大数据、NoSQL、AI的交互。
- 使用数据存储（data vaulting）技术对数据仓库中的历史数据进行审计、跟踪、检查
- 开发一致且可重复的ETL（提取、转换、加载）过程
- 构建和部署高度可扩展且可重复的仓库

受众

- 数据建模师
- 数据仓库专家
- 商业智能专家
- 数据工程师
- 数据库管理员

课程形式

- 部分讲座、部分讨论、练习和大量实操