Summary
OLAP and data warehousing are both used in the context of specific database-design patterns, where a database is used for analysis and reporting. In contrast to OLTP, OLAP deals with bigger amounts of data and a smaller number of concurrent sessions and transactions, but the amount of changes within a transaction usually is bigger. The database structure is often denormalized to improve query performance. A database that is a part of an OLAP solution is often called a data warehouse.
In this chapter, we discussed structuring data in a data warehouse, how to load data there, and how to optimize the database performance by applying partitioning, and using parallel query execution and index-only scans.
In the next chapter, we will discuss ...
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