As companies consider their ability to manage the asset that is information, the data warehouse platform (and its database management system, or DBMS) is the most important decision point. The platform is the foundational component of the tool selections, the consultancy hires, the architecture, etc. In short, it defines your information culture.
However, in selecting the platform to support the data warehouse, organizations are faced with an exponentially higher number of variations and distinct departures from the traditional online transactional processing (OLTP) database management systems than ever before.
Over time, data warehouse data volumes will continue to soar as organizational history accumulates, syndicated data is collected and new sources with more detailed data are added. Furthermore, the community consuming the data continues to grow, expanding well beyond company boundaries to customers, supply chain partners and even users on the Internet. Companies need to make sure they choose a proven platform not just for the initial known requirements but also one with the ability to scale to future, to-be-determined requirements.
The strategy for developing a data warehouse can be broken down into three steps.
1. Determine business requirements. Not all data warehouses are the same. You need to understand why the requestor needs a data warehouse. You'll need to tie those objectives to what data sources you'll be pulling data from, what subject areas, what business rules you'll follow and what users and/or applications you'll support.
2. Make a timeline. Break up those business objectives mentioned above into 3-month incremental deliverables.
3. Choose architecture, methodology, and technology and compile a staff. You'll need to meet the business objectives as well as build your structures scalable so that you can add-on easily to meet future requirements. This includes securing business involvement with governance and stewardship programs.
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