Data Warehouse vs Data Mart

I see a lot of confusion on what exactly is the difference between a data warehouse and a data mart.  The best definition that I have heard of a data warehouse is:

“A relational database schema which stores historical data and metadata from an operational system or systems, in such a way as to facilitate the reporting and analysis of the data, aggregated to various levels”.

Or more simply:

“A single organizational repository of enterprise wide data across many or all subject areas”.

Typical data warehouses have these characteristics:

  • Holds multiple subject areas
  • Holds very detailed information
  • Works to integrate all data sources
  • Does not necessarily use a dimensional model but feeds dimensional models.

On the other hand, a data mart is the access layer of the data warehouse environment that is used to get data out to the users.  The data mart is a subset of the data warehouse which is usually oriented to a specific business line or team (Finance has their data mart, marketing has theirs, sales has theirs and so on).

According to the Inmon school of data warehousing, a dependent data mart is a logical subset (view) or a physical subset (extract) of a larger data warehouse, usually isolated for the need to have a special data model or schema (e.g., to restructure for OLAP).  One of the benefits of the new Tabular mode in SSAS is that you can build that on top of a data warehouse instead of a data mart, saving time by not having to build a data mart.

So in short, I like to think of a data warehouse as containing many subject areas, and a data mart as containing just one of those subject areas.

More info:

Data Mart vs Data Warehouse – The Great Debate

Data Warehouse Architecture – Kimball and Inmon methodologies

Data Mart Does Not Equal Data Warehouse

Data mart or data warehouse?

Data Warehouse – Data Mart

Data Warehouse vs Data Mart

About James Serra

James currently works for Microsoft specializing in big data and data warehousing using the Analytics Platform System (APS), a Massively Parallel Processing (MPP) architecture. Previously he was an independent consultant working as a Data Warehouse/Business Intelligence/MDM architect and developer, specializing in the Microsoft BI stack. He is a SQL Server MVP with over 25 years of IT experience.
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2 Responses to Data Warehouse vs Data Mart

  1. Pingback: Why You Need a Data Warehouse - SQL Server - SQL Server - Toad World

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