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A data warehouse is an organization’s huge repository for accumulated data from many different sources. The usual purpose of this is to examine the data and make smarter business decisions.
The strategic use of data is facilitated by the integration of numerous technologies and components. A business stores a lot of data electronically with the intention of using it for analysis and research rather than transaction processing. It involves transforming data into information and quickly making it available to consumers so that it can have an impact.
The inventor of the data warehouse, computer scientist William Inmon, described four distinctive qualities that enable data warehouses to provide this overall advantage.
Subject-oriented: They are capable of conducting data analysis on a certain topic or job function.
Integrated: Data warehouses bring many data kinds from various sources into uniformity.
Nonvolatile: Data that has been stored in a data warehouse is constant and stable.
Time-variant: Analysis of data warehouses considers changes throughout time.
A data warehouse can be built or organized in a variety of ways depending on the organization’s requirements. The primary elements of the data warehouse architecture are the hardware used, the software developed, and the data resources specifically needed for a data warehouse to work correctly. Every data warehouse has several stages during which the organization’s requirements are adjusted and refined.
Big Data and SQL 