Key component of big data solution
SQL Data Warehouse stores data into relational tables with columnar storage. This format significantly reduces the data storage costs, and improves query performance. Once data is stored in SQL Data Warehouse, you can run analytics at massive scale. Compared to traditional database systems, analysis queries finish in seconds instead of minutes, or hours instead of days.
The analysis results can go to worldwide reporting databases or applications. Business analysts can then gain insights to make well-informed business decisions.

Data Warehouse combines massively parallel processing (MPP) with Azure storage to achieve high performance and scalability
MPP architecture componentsSQL Data Warehouse leverages a scale out architecture to distribute computational processing of data across multiple nodes. The unit of scale is an abstraction of compute power that is known as a data warehouse unit. SQL Data Warehouse separates compute from storage which enables you to scale compute independently of the data in your system.
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