# Data Mart vs Data Warehouse

Big Data

September 27, 2022

### 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 Data warehouse

## 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.