Azure Data Lake analytics is one of the flagship services from Azure to execute analytics jobs. Azure Data Lake stores took care of storing big data in an optimized way. However, for an end-to-end scenario, the data in storage is useful if it is read by a service and that service can perform analytics on it and gain meaningful insights. The analytics service is compute intensive in nature because of deep processing of a large quantity of data. To setup an environment for such a service involves provisioning and configuring virtual machines, tune them for performance and maintain them. Azure Data Lake analytics provides platform as a service capability for running analytics jobs. It means users no more need to think about provisioning and configuring infrastructure and hardware, rather, they can concentrate on writing their analytics job and focus on the business problem.

Azure Data Lake analytics provides its own SQL-style language U-SQL that has a capability to integrate code generally written using programming languages, such as C#. It's a versatile language that can query multiple types of databases, such as Azure SQL, IaaS SQL Server, and Azure SQL data warehouse.

Another important benefit, apart from low maintenance, is that it provides the pay-as-you-go model from a cost perspective. Users pay only when the analytic jobs are running and not otherwise. There is no charge for provisioning Azure Data Lake analytics if it is not running.

Azure Data Lake analytics is a scalable service. It means that when a job executes in Azure Data Lake analytics, it provisions compute and memory resources behind the scene and dynamically keeps scaling out as more demand for resource happens. After the job completes, the resources are scaled down automatically. All this happens transparently without the knowledge of the user.

Azure Data Lake analytics just as Azure Date Laka store, is integrated with Azure AD for authentication purpose. Users, groups, and service applications available in Azure AD can access Azure Date Laka analytics. ARM's RBAC is also applied from an authorization perspective to determine the permissions applicable for users and Azure Date Laka analytics.