Azure SQL Data Warehouse Training

This hands-on, instructor-led training at your facility helps data warehouse developers and administrators adopt the MPP architecture found in Azure SQL Data Warehouse for scalable, high-performance analytics in the cloud. Up to ten attendees will receive expert-led guidance through a complete set of hands-on labs and training modules. After the training, attendees will be able to accurately plan for data warehouse migrations from on-premises to Azure SQL Data Warehouse, effectively write D-SQL queries that are fully distribution compatible, and expertly administer the environment to ensure that your data warehouse is running at peak performance no matter what size it grows to.

Day 1: Introduction

Learn about massively parallel processing (MPP) architecture. Glance under the hood of Azure SQL DW and understand how it’s put together. Explore table geometry including Distributions, Partitions, and more. Configure development environment and work through hands-on labs.

Day 2: Development Patterns

Learn common development techniques used with Distributed SQL (DSQL) and Azure SQL DW. Load data into the environment using Polybase. Explore how to migrate existing databases to Azure SQL DW. Work through basic query tuning exercises.

Day 3: Administration

Scale performance of your Azure SQL DW with Data Warehouse Units (DWUs). Explore concurrency options and the ability to control how many users are able to work at the same time. Monitor performance with graphical interfaces and non-graphical interfaces with DSQL. Take codes samples of basic database maintenance back to your office.

Day 4: Kickstart your Data Warehouse

Learn how to migrate existing ETL to Azure SQL DW compliant development patterns. Explore additional Azure tools and how they integrate with Azure SQL DW. Fire up Power BI and explore data visualization and reporting against massive data. Finish with a facilitate session that can include a look at how your own data will look in Azure SQL DW, or a planning session for migrating a larger solution to Azure.