Data Warehouse v/s Data Marts: Key Differences

📊 Data Bits
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Hey everyone👋

Check out this article highlighting the differences between a Data Warehouse & a Data Mart

:zap: Here are the major highlights from the article:

Key Differences

  1. Size and Scope

Data warehouses are designed to handle large volumes of data from multiple sources, while data marts are typically smaller and more focused.

  1. Purpose

Data warehouses are designed to provide a single source of truth for the entire organization, while data marts serve a specific business function or department.

  1. Data Model

Data warehouses typically use a dimensional data model optimized for reporting and analysis. Data marts can use either a dimensional or a normalized data model, depending on the business’s specific needs.

  1. Data Integration

Data warehouses are designed to integrate data from multiple sources, while data marts are typically created to support a specific business function or department and may not need to integrate data from multiple sources.

  1. Implementation

Data warehouses are typically more complex and time-consuming to implement than data marts. Data marts can be created more quickly and with less effort, making them a more agile and flexible option for businesses that need to respond quickly to changing business needs.

To learn more, checkout the full article here⤵️

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