What is Data Mart ?

Data Mart is very similar to a Data Warehouse but limited in scope and purpose and is usually associated to one single domain. Often people get confused between Data Warehouse and Data Marts.
I have already written before about the Data Warehouse and need of Data Warehouse. If you have missed the same , you can read here : What is Data Warehouse ?
This article will give you an introduction to Data Mart, why it is needed  and different types.

What is Data Mart ?

Data Mart is a decentralized subset of data found either in Data Warehouse or as a standalone subset designed to support the unique business unit requirements of a specific decision support system. Data Marts have specific business related purposes such as measuring the impact of marketing promotions, or measuring and forecasting sales performance and so on.

A Data Mart is a subset of Data Warehouse.

Need Of Data Mart :

  • End users will  get much better performance querying from a Data Mart than from a Data Warehouse.
  • End users will have a much easier time navigating through Data Mart due to lesser amount of data.

Features Of Data Mart :

  • Low Cost
  • Controlled locally rather than centrally, conferring power on the user group.
  • Contains less information than the warehouse
  • Rapid response
  • Easily understood and navigated than an enterprise Data Warehouse.
  • Within the range of divisional and departmental budgets.

Types Of Data Mart :

  1. Dependent  :- Allows to unite organization’s data in one data warehouse.
  2. Independent  :- Created without the use of central data warehouse.
  3. Hybrid  :- Allows to combine inputs from sources other than data warehouse.

Advantages of Data Mart :

  • Typically single subject area and fewer dimensions.
  • Limited feeds
  • Very quick time to market (30-120 days to pilot)
  • Quick impact on bottom line problems.
  • Focused user needs.
  • Limited scope.
  • Optimum model for DW construction

Disadvantages of Data Mart :

  • Does not provide integrated view of business information.
  • Uncontrolled proliferation of data marts result in redundancy
  • More number of data marts complex to maintain
  • Scalability issues for large number of users and increased data volume.

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