Big data applications: Real-world strategies for managing big data
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A data warehouse is a federated repository for all the data that an enterprise's various business systems collect. The repository may be physical or logical.
Data warehousing emphasizes the capture of data from diverse sources for useful analysis and access, but does not generally start from the point-of-view of the end user who may need access to specialized, sometimes local databases. The latter idea is known as the data mart.
There are two approaches to data warehousing, top down and bottom up. The top down approach spins off data marts for specific groups of users after the complete data warehouse has been created. The bottom up approach builds the data marts first and then combines them into a single, all-encompassing data warehouse.
Typically, a data warehouse is housed on an enterprise mainframe server or increasingly, in the cloud. Data from various online transaction processing (OLTP) applications and other sources is selectively extracted for use by analytical applications and user queries.
The term data warehouse was coined by William H. Inmon, who is known as the Father of Data Warehousing. Inmon described a data warehouse as being a subject-oriented, integrated, time-variant and nonvolatile collection of data that supports management's decision-making process.
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