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Difference between Data Warehouse and Data Mart

Updated: Dec 21, 2023

A data warehouse and a data mart serve similar purposes, but they have several key differences in scope, data sources, users, and purpose:


Data Warehouse


1. Scope: A data warehouse is a large, centralized repository of data that contains the entire organization's historical data. It's designed to support decision-making across the entire organization.

2. Data Sources: Data warehouses draw data from multiple disparate sources across an organization. This data is cleaned, transformed, and integrated before being stored.

3. Users: Data warehouses are designed for use by decision-makers at all levels of the organization.

4. Purpose: The main purpose of a data warehouse is to provide an organization-wide, unified, and consistent view of business operations to enable informed decision-making.


Data Mart


1. Scope: A data mart is a subset of a data warehouse that is generally oriented to a specific business line or team.

2. Data Sources: Data marts usually pull data from a few specific sources related to a particular department or subject.

3. Users: Data marts are designed for use by a specific team or department within the organization.

4. Purpose: The main purpose of a data mart is to meet the specific demands of a particular business function or department.


In summary, while a data warehouse is designed for an enterprise-wide perspective, a data mart is more localized and focused, aimed at meeting the requirements of a specific department or business function. It's important to note that data marts can be a part of the larger data warehouse system. In some organizations, multiple data marts are used, each for a specific business purpose, and they all feed into the central data warehouse.

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