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James Serra's Blog

James is currently a Senior Business Intelligence Architect/Developer and has over 20 years of IT experience. James started his career as a software developer, then became a DBA 12 years ago, and for the last five years he has been working extensively with Business Intelligence using the SQL Server BI stack (SSAS, SSRS, and SSIS). James has been at times a permanent employee, consultant, contractor, and owner of his own business. All these experiences along with continuous learning has helped James to develop many successful data warehouse and BI projects. James has earned the MCITP Business Developer 2008, MCITP Database Administrator 2008, and MCITP Database Developer 2008, and has a Bachelor of Science degree in Computer Engineering. His blog is at .

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.

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

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