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Data mart vs. Data warehouse



Data Warehouse

Data Warehouse is a system used for reporting and data analysis. DWs are central repositories of integrated data from one or more disparate sources. They store current and historical data and are used for creating analytical reports for knowledge workers throughout the enterprise. Examples of reports could range from annual and quarterly comparisons and trends to detailed daily sales analyses. Users of the data warehouse perform data analyses that are often time-related.

  • Holds multiple subject areas
  • Holds very detailed information
  • Works to integrate all data sources
  • Does not necessarily use a dimensional model but feeds dimensional models.


Data Mart

A data mart is a simple form of a data warehouse that is focused on a single subject (or functional area), such as sales, finance or marketing. Data marts are often built and controlled by a single department within an organization.  Given their single-subject focus, data marts usually draw data from only a few sources. The sources could be internal operational systems, a central data warehouse, or external data.[1] Denormalization is the norm for data modeling techniques in this system.

  • Often holds only one subject area- for example, Finance, or Sales
  • Can be created mush faster than data warehouse due to its limited coverage
  • May hold more summarised data (although many hold full detail)
  • Concentrates on integrating information from a given subject area or set of source systems
  • Is built focused on a dimensional model using a star schema.

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