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Data Warehouse vs Data Mart September 14, 2009

Posted by sendtoshailesh in OLAP.
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Data Warehouse

Data Mart

Scope & Application

Application Independent

A Data Warehouse is single point repository and its data can be used for any foreseeable application

Specific Application

Data-Mart is created out of a specific purpose. This means that you will have a data mart created to analyze customer value. This means that the designer of the data-mart is aware that the data will be used for OLAP, what kind of broad queries could be placed.

Domain Independent

The Data Warehouse can be used for any domain including Sales,Customer, operations, finance etc.

Specific Domain

A Data-mart is specific to a given domain. You will generally not find a data mart , which serves Sales as well as operations domain at the same time.

Centralized Independent

The control and management of data warehouse is centralized.

Decentralized by User Area

Typically a data-mart is owned by a specific function/sub-function.

Planned

Data Warehouse is a strategic initiative, which comes out of a blueprint. It is not an immediate response to an immediate problem. It has many foundation elements, which cannot be developed in an ad-hoc manner. For example, the standard sets of dimensions & measures.

Organic, possibly not planned

Data-Mart is a response to a critical business need. It is developed to provide gratification to the users, and given that it is owned & managed at a functional level, it grows with time.

Data

Historical, Detailed & Summarized

A good data warehouse will capture the history of transactions by default; even of there is no immediate need. This is because a data-warehouse always tries to be future proof.

Some history, detailed and summarized

It’s same with Data Warehouse. However, the level of history that is captured is governed by the business need. For example, a data warehouse will capture the changes in the customer marital status by default. A Data Mart may not do it, if Data Mart is created to profile/segment a customer on the basis of his spending patterns only.

Sources

Many Internal & external Sources

This is an obvious outcome of the Data Warehouse being a generic resource. That is also the reason why the staging design for a data warehouse takes much more time compared to that of a data mart.

Few Internal & External Sources

Self Explanatory- A limited purpose leads to limited sources.

Life Cycle

Stand-Along Strategic Initiative:

A Data Warehouse is an outcome of a company’s strategy to make data an enterprise resource. If there is any other trigger, chances are that it may not achieve its objectives

Typically part of a Business Project:

A Data Mart comes into being due to a business need. For example Risk Portfolio Analysis data mart could be a part of Enhancing Risk Management Initiative.

Long life

A Data Warehouse is a long-term foundation of an enterprise.

Can have any life span

A Data Mart starts with a given objective, and it can have a life span ranging from one year to endless. This is because some applications are core and business as usual to an enterprise. The life a data mart could be shortened, if a Data Warehouse comes into being.

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