Data Warehouse Features
The term “Data Warehouse” was first coined by Bill Inmon in 1990. According to Inmon, a data warehouse is a subject oriented, integrated, time-variant, and non-volatile collection of data. This data helps analysts to take informed decisions in an organization.
Data Warehouse Features
The key features of a data warehouse are discussed below:
- Subject Oriented – A data warehouse is subject oriented because it provides information around a subject rather than the organization’s ongoing operations. These subjects can be product, customers, suppliers, sales, revenue, etc. A data warehouse does not focus on the ongoing operations, rather it focuses on modelling and analysis of data for decision making.
- Integrated – A data warehouse is constructed by integrating data from heterogeneous sources such as relational databases, flat files, etc. This integration enhances the effective analysis of data.
- Time Variant – The data collected in a data warehouse is identified with a particular time period. The data in a data warehouse provides information from the historical point of view.
- Non-volatile – Non-volatile means the previous data is not erased when new data is added to it. A data warehouse is kept separate from the operational database and therefore frequent changes in operational database is not reflected in the data warehouse.
Note: A data warehouse does not require transaction processing, recovery, and concurrency controls, because it is physically stored and separate from the operational database.
