Difference Between Data Warehouse and Data Mart

Differences Data Storage Data Visualization

Both data warehouses and data marts serve the same purpose; they are data repositories. However, we can differentiate a data warehouse from a data mart on the basis of the amount of data they can store. A data warehouse a large repository of data that is collected from different organizations, whereas a data mart is a logical subset of a data warehouse.

Read this article to find out more about data warehouses and data marts and how they are different from each other. Let's start with a basic overview of the two.

What is a Data Warehouse?

Data Warehouse is a large repository of data that is collected from different organizations within a corporation. Thus, the data warehouse represents a time variant, non−volatile and integrated set of data that helps the management in the decision making process. In other words, a data warehouse is a large group of data and information collected from multiple sources, and stored in a unified schema.

Data warehouses use a centralized system. They use slightly de−normalized data and follow top−down data model. The characteristics of a data warehouse includes flexibility, longer life, data−orientation, etc. But, it can be a difficult task to design a data warehouse because they have a continuously evolving structure.

What is a Data Mart?

A Data Mart is basically a subtype of data ware house. In other words, a data mart is a subset of data corresponding to a certain set of users. Data marts are mainly used to make tactical decisions for businesses. In a data warehouse, there are several departmental and logical data marts that must be strong enough in their data illustration to ensure the robustness of the data warehouse.

The process of designing a data mart is comparatively easy because they handle small volumes of data. Data marts are implemented on low−cost departmental servers, and their implementation is monitored weekly.

Based on the source of data they handle, data marts can be grouped into two different categories− dependent data marts and independent data marts.

Difference between Data Warehouse and Data Mart

The following table highlights the important differences between a Data Warehouse and a Data Mart −

Key	Data Warehouse	Data Mart
Definition	It is a large repository of data that is collected from different organizations within a corporation.	It is a subtype of a data warehouse.
Use	It helps to make a strategic decision.	It helps to make tactical decisions for business.
Objective	The main objective is to provide an integrated environment and coherent image of the business.	It is designed to meet the requirement of a specific user group.
Design	The designing process of a data warehouse is quite complex. It may or may not be used in a dimensional model. It can feed dimensional models.	It is relatively easy to design a data mart. It is generally used in the business division at the departmental level. It is built by focusing on a dimensional model.
Ease of use	It includes data from a several organizations, hence it takes a long time to process the data from a data warehouse.	Data marts are easy to implement and use. They can handle only small volumes of data.

Conclusion

Although data warehouses and data marts serve the same purpose, they are different from each other in many aspects, as discussed in the above table. The most significant difference is that a data warehouse is an application-independent large repository of data, whereas a data mart is a logical subset of a data warehouse that is specific to a decision support system application.