Data Mart vs Data Warehouse

In this article we are going to compare the differences between a Data mart and a Data Warehouse

Data Marts created from a Data Warehouse

So, it is easy to say that a Data Mart and a Data Warehouse are the same thing and Business Analysts, and other data consumers use those terms inter-changeably. The fact is that a Data Warehouse can consist of many Data Marts makes the opening statement true. When you examine the parts of Data Mart you start seeing how it can be a part of a Datawarehouse

Data Marts

Lets’ look at Data Marts and the problems they solve. At high level Data Marts are often implemented at the Business Unit level. An examples of this is a Sales Departments that uses a data mart comprised of pending and closed sales results, Supply Chain uses a data mart for managing the inventory, or Accounting uses a data mart for managing revenue. So, each department has specific data of interest that may or may not be different than the other departments. The parts of a data mart can be summarized as

PROS

• Cost: $10,000 and up
• Setup Time: Months
• Normalization: Can be normalized or denormalized

CONS

• Data Sources: Relatively few data sources
• Focus: A single organizational area or Line of Business
• Data Stored: Usually summarized business specific data

Data Warehouse

Now let’s look at a Data Warehouse implemeneted at the enterprise level and captures all of the business data, and data schema and is often controlled by a centralized group like a corporate IT department that supports the different business units. A data warehouse consumes information from many different sources to support all lines of business. It is from the data warehouse that business units develop their respective data marts.

PROS

• Focus: Enterprise-wide repository of disparate data sources
• Data Stored: Raw, Summarized, and Meta
• Data Sources: Many external and internal sources from different areas of an organization
• Normalization: Depends on Use Case however is commonly denormalized for performance
• Decision Types: Enterprise wide and includes all lines of business

CONS

• Cost: $100,000 and up
• Setup Time: One or more years
• Size: Very Large often Terabytes in size
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Conclusion

Dont be one of those companies either small or large that overlooks the importance of using a Data Warehouse. If you find your company needs help with creating, managing, or maintaining a Data Warehouse, Explait is here to help