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Difference between Data Warehouse and Data Mart

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Both Data Warehouse and Data Mart are used for store the data. 

The main difference between Data warehouse and Data mart is that, Data Warehouse is the type of database which is data-oriented in nature. while, Data Mart is the type of database which is the project-oriented in nature. The other difference between these two the Data warehouse and the Data mart is that, Data warehouse is large in scope where as Data mart is limited in scope. 

Let’s see the difference between Data warehouse and Data mart:

Sl.No Data Warehouse Data Mart
1. Data warehouse is a Centralised system. While it is a decentralised system.
2. In data warehouse, lightly denormalization takes place. While in Data mart, highly denormalization takes place.
3. Data warehouse is top-down model. While it is a bottom-up model.
4. To built a warehouse is difficult. While to build a mart is easy.
5. In data warehouse, Fact constellation schema is used. While in this, Star schema and snowflake schema are used.
6. Data Warehouse is flexible. While it is not flexible.
7. Data Warehouse is the data-oriented in nature. While it is the project-oriented in nature.
8. Data Ware house has long life. While data-mart has short life than warehouse.
9. In Data Warehouse, Data are contained in detail form. While in this, data are contained in summarized form.
10. Data Warehouse is vast in size. While data mart is smaller than warehouse.
11. The Data Warehouse might be somewhere between 100 GB and 1 TB+ in size. The Size of Data Mart is less than 100 GB.
12. The time it takes to implement a data warehouse might range from months to years. The Data Mart deployment procedure is time-limited to a few months.
13. It uses a lot of data and has comprehensive operational data. Operational data are not present in Data Mart.
14.  It collects data from various data sources. It generally stores data from a data warehouse. 
15. Long time for processing the data because of large data. Less time for processing the data because of handling only a small amount of data.
16. Complicated design process of creating schemas and views. Easy design process of creating schemas and views.

Last Updated : 05 May, 2023
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