An organization, how-much-so ever big or small it is, should not start with a big-bang enterprise data warehouse. It should start with few high importance Data-Marts. The reasons are as follows:
An Enterprise Data Warehouse is a long term commitment: This means that there are many imperatives (or foundations), which are key for a Data Warehouse. The examples of these imperatives are foundation or conformed dimensions, fine-grained granular data, comprehensive star-schemas etc…An organization will need high level of readiness and investments to build these foundations. These foundations (though great for data marts as well) can be compromised for initial set of Data-marts.
Business Learning- Initial set of data-marts will provide great learning, less on the IT side and more on the business side. Here are the set of learnings from business side:
- • Creating business themes
- • Building Data-Mart Business Requirements
- • Building Dimensional Model
- • Testing of Data-Mart
- • Taking business decisions around the extraction and transformation
- • Generating the information out of the Data-Mart through end-user tools (like reporting and analytics application)
Examples of IT Learnings:
- • Extraction, Transformation and Loading design
- • Processing Load Management
- • Handling Data Explosion (data goes up exponentially as you add sparse fields- where most of the records are blank)
- • Change Management (end-to-end impact analysis if you make a change in the Data Mart Model)
Show-case for sponsors: A successful Data-Mart may make the sponsorship of a Data Warehouse much easier.
Quick-hit: A Data-mart is a quick hit and gives earlier gratification to business.
Non-Disruptive: It does not take away the attention of an organization from other big things.
You can refer my portal Business Intelligence and Performance Management for more details.
