Azure Data Lake enables you to collect data of any size, type, and velocity in one place in order to explore, analyze, and process the data using tools and languages such as U-SQL, Apache Spark, Hive, HBase, and Storm. It works with existing IT investments for identity, management, and security for simplified handling and governance. It also integrates easily with operational stores and data warehouses.

Data Lake consists of two primary elements: Azure Data Lake Store and Azure Data Lake Analytics. Data Lake Store is an enterprise-wide hyper-scale repository for big-data analytical workloads. It was built from the ground up to support massive throughput and integrates with Apache Hadoop by acting as an HDFS distributed file system. It also supports Azure Active Directory for access control independent of Hadoop. Data Lake Analytics is an easy-to-learn query and analytics engine that features a new query language called U-SQL, which combines elements of traditional SQL syntax with powerful expression support and extensibility. It integrates seamlessly with Data Lake Store so you can execute queries against multiple disparate data sources as if they were one. This lab will introduce Data Lake Store and Data Lake Analytics and walk you through typical usage scenarios for each.


In this hands-on lab, you will learn how to:

  • Create Data Lake Stores
  • Create Data Lake Analytics accounts and connect them to Data Lake Stores
  • Import data into Azure Data Lake Stores
  • Run U-SQL jobs in Azure Data Lake Analytics
  • Federate Azure SQL Databases and query them with U-SQL


The following are required to complete this hands-on lab:


Click here to download a zip file containing the resources used in this lab. Copy the contents of the zip file into a folder on your hard disk.