Difference between Data Mart and Data Warehouse

A data warehouse is a large centralized repository of data that contains information including historical data from many sources within an organization.

A data mart is a subset of a data warehouse that is focused on a single subject or line of business, such as finance, sales, or marketing.


Data mart VS Data warehouse

Data MartData Warehouse
In a data mart, the data collected for analysis is based only on one single subject area. For example finance or sales.In a data warehouse, the data collected for analysis is based on multiple subject areas.
Data mart captures data from a data warehouse or operational systems or external sources.The data warehouse captures data from multiple data sources.
In data mart, data can be normalized.In a data warehouse, data is highly denormalized.
Data mart occupies less storage area(less than 100GB).The Data warehouse occupies more storage area(minimum 100GB).
A data mart can be developed between 6-8 months of duration.A data warehouse takes 1-2 years for developing completely.
Maintenance overhead is less in the data mart.Maintenance overhead is more.
The main objective of a data mart is to store and use data by a specific user community.The main objective of a data warehouse is to support business intelligence, batch reporting, and data visualization.
In the case of a data mart, a repository of data is designed to serve a particular community of knowledge workers. The Data warehouse contains a central location that stores consolidated data from multiple sources(various databases).


Here in this blog, we discussed the differences between a data mart and a data warehouse. We knew that a data mart is the subset of a data warehouse that holds more summarized data whereas a data warehouse very detailed information.

A data mart is specially built and focused on a dimensional model using a star schema whereas a data warehouse doesn’t need to be built using a dimensional model but rather it feeds dimensional models.

A data mart is more concentrated on integrating information from a specified subject area that could be either finance, sales, or marketing whereas a data warehouse works to integrate all data sources that are generated from the particular organization branches and sub-branches.

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