Data WareHousing Concepts

The principal notion behind data warehousing is that the data stored for business analysis can most efficiently be accessed by dividing it from the data in the operational systems. A data warehouse, therefore, is a collection of data gathered from one or more data repositories to create a new, central database. For example an industry may create a data warehouse by extracting the operational data it has accumulated concerning the workers information, products they are working on, material they are using for making the particular product, output production and etc,. Data Warehousing is not just the data in the warehouse, but also the architecture and tools to collect, query, analyze and present information.

The characteristics of a data warehouse were first defined by W.H. Inmon who stated, “A data warehouse is subject-oriented, integrated, time-variant and non-volatile [data] collection in support of management decision making processes”. Let’s discuss  that definition down

  • Subject-oriented: all relevant data concerning a subject
  • Integrated: all data in the warehouse must be compatible with each other regardless of type or location.
  • Time-variant: all data contains a reference to time so that the age of each piece of data can be determined.
  • Non-volatile: the data does not change once it has been collected.