What is Data Warehouse?
There are two different definitions of data warehouse defined by Ralph Kimball and Bill Inmon
Bill Inmon Says
A warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management’s decision making process”.
Ralph Kimball Says
Data warehouse is the conglomerate of all data marts within the enterprise. Information is always stored in the dimensional model.
Textbook definition of Data warehouse:
“A data warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management’s decision making process.”
Subject-Oriented: Datawarehouse id subject oriented means its is focused towards one subject area e.g. Marketing or Sales
Integrated: Datawarehouse is integrated means it combines data from multiple sources and to be presented in single form e.g. Data can be pulled from sales and marketing department and put in datawarehouse in order to get total yearly revenue. There will single definition of revenue for all departments.
Time-Variant: Generally historical data is help in a data warehouse to represent changes or history of data. It totally depends on the administrator to decide how old data can be kept in Datawarehouse. e.g 1 year, 5 year. etc.
Non-volatile: There will be no update in the data stored in datawarehouse in stead different version of data will be held to show changes.
As per Mr. Kimball “A data warehouse is a copy of transaction data specifically structured for query and analysis”
There is no right or wrong definition of the data warehouse, above two definitions represents two different approach of data warehouse. However in realty you will find enterprise data warehouse to be close to Ralph Kimball’s idea of data warehouse as most of the as need of data warehouse started as a requirement of departmental reporting need and gradually grown towards enterprise data warehouse.
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