When you need to scale your data warehouse's storage and processing capabilities in minutes, not months, you need a cloud-based massively parallel processing solution.
In this computer science course, you will learn how to deploy, design, and load data using Microsoft's Azure SQL Data Warehouse, or SQL DW. You'll learn about data distribution, compressed in-memory indexes, PolyBase for Big Data, and elastic scale.
Note: To complete the hands-on elements in this course, you will require an Azure subscription. You can sign up for a free Azure trial subscription (a valid credit card is required for verification, but you will not be charged for Azure services). Note that the free trial is not available in all regions. It is possible to complete the course and earn a certificate without completing the hands-on practices.
What you'll learn
In this course, you’ll learn theory and techniques for:
Choosing a massively parallel processing architecture for a cloud-based data warehouse.
Designing tables and indexes to efficiently distribute data in tables across many nodes.
Loading data from a variety of sources, querying using PolyBase, securing and recovering data, and integrating into Big Data environments.
Familiarity with database concepts and basic SQL query syntax Familiarity with the reporting and analytics needs of users A willingness to learn actively and persevere when troubleshooting technical problems is essential
Meet the instructors
SQL Server Premier Field Engineer
Theresa Iserman is a SQL Server Premier Field Engineer at Microsoft. She’s a trusted technical advisor, trainer, & troubleshooter and supports Microsoft’s enterprise customers in optimizing their SQL Server implementations. Theresa holds an MCSA: Cloud Platform certification and has been working with data for over 15 years. Her past roles include working on transactional & data warehouse systems, web application development, & technical project management. You can follow Theresa on Twitter at: @TheresaIserman.
Cloud and Devices
Scott Klein is CTO of Cloud and Devices. He's a lover of data, analytics and IoT. You can follow Scott on Twitter at: @SQLScott