Solutii si servicii cloud
Cloud Data Warehouse Solution

Key component of big data solution

In a cloud data solution, data is ingested into big data stores from a variety of sources. Once in a big data store, Hadoop, Spark, and machine learning algorithms prepare and train the data. When the data is ready for complex analysis, SQL Data Warehouse uses PolyBase to query the big data stores. PolyBase uses standard T-SQL queries to bring the data into SQL Data Warehouse.

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 components
SQL 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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