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9 January 2023

Difference Between Data Warehouse and Data Mart

The main difference between a data warehouse and a data mart is that a data warehouse is a type of database that is data oriented in nature. While data mart is a type of database that is project-oriented in nature. Let us discuss some more differences between Data Warehouse and Data Mart with the help of the comparison given below.

What is a Data warehouse?

In order to offer useful business insights, a data warehouse gathers and handles data from many sources. It is a database that supports the company's decision-making and is independent of the operational systems. Data is kept in a data warehouse using a historical lens. The warehouse data comes from a variety of functional divisions. After being examined and purified, it is subsequently with the data warehouse system.  An extremely fast computer system with a lot of storage was employed by the data warehouse. This tool can respond to any complicated data-related inquiries.

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What is Data mart?

A data warehouse can be expressed simply as data. It focuses on only one thing. Only a few sources are used by data mart to gather its data. These sources might be an internal operating system, a central data warehouse, or external data sources. An index and extraction system is a data mart. This part of a data warehouse is crucial. It is subject focused and created with a particular user demographic in mind. Data marts are quick and simple to use when compared to data warehouses since they employ modest quantities of data. 

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Difference between data warehouse and data mart:

  • The data warehouse is a centralized system. While Data mart is a decentralized system.
  • In data warehouses, light denormalization takes place. While in a data mart, high denormalization takes place.
  • A data warehouse is a top-down model. Data mart, however, uses a bottom-up approach.
  • Building a warehouse is difficult. While to built a data mart is easy.
  • Data warehouse and fact constellation schema is used. While in a data mart, star schema and snowflake schema are used.
  • The data warehouse is flexible. While data mart is not flexible.
  • The data warehouse is data-oriented in nature. Data mart, meanwhile, is more project-focused.
  • A data warehouse has a long life. While data mart has short life than the warehouse.
  • A data warehouse is vast in size. While a data mart is smaller than a warehouse.
  • In a data warehouse, data are contained in a detailed form. While in a data mart, data are contained in summarized form.
  • Data warehouses collect data from various data sources. While data mart generally stores data from a data warehouse. 
  • In data ware, long time for processing the data because of large data. While in a data mart less time for processing the data because of handling only a small amount of data.
  • A data warehouse is a complicated design process of creating schemas and views. While in data mart is an easy design process of creating schemas and views. 
  • Data warehouse helps to take a strategic decision. While in data mart helps to take tactical decisions for the business.
  • The main objective of a data warehouse is to provide an integrated environment and a coherent picture of the business at a point in time. A data mart is mostly used in the business divisions at the department level.
  • Data warehousing includes a large area of the corporation which is why it takes a long time to process it. Data marts are easy to use, design, and implement as they can only handle small amounts of data. 
  • The size of the data warehouse may range from 100 Gb to 1 TB+. The size of the data mart is less than 100GB. 
Thanks for reading the article. Still, if you have any questions or queries in your mind on the set Difference Between Data Warehouse and Data Mart then please ask us in the comment section below.

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