Principles for Enterprise Data Warehouse Design

Data warehousing is not a stagnant technology; it's alive and kicking. Indeed, most companies deploy data warehousing technology to some extent, and many have an enterprise-wide DW.

However, as with any technology, a DW can quickly become a quagmire if it's not designed, implemented and maintained properly. With this in mind, there are few principles that can help us us start - and keep - our DW design and implementation on the road to achieving our desired results. there total 7 business and IT principles because most IT issues really involve business and IT equally.

Business Principles
Organizational Consensus(Agreements):
Make every effort to gain acceptance for, and minimize resistance to, the DW. If we can involve the stakeholders early in the process, they're much more likely to embrace the DW, use it and, hopefully, champion it to the rest of the company.
Data Integrity:
Data warehousing - of any business intelligence (BI) project - is a single version of the truth about organizational data. Any design for DW should begin by minimizing the chances for data replication and inconsistency. It should also promote data integration and standardization. Any reasonable methodology we can choose to achieve data integrity should work, as long as we can implement the methodology effectively with the end result in mind.
Implementation Efficiency:
To help meet the needs of company as early as possible and minimize project costs, the DW design should be straightforward and efficient to implement. This is basic fundamental design issue. we can design a technically DW, but if that design is difficult to understand or implement or doesn't meet user needs, our DW project will be in difficulty and cost can be increase.
User Friendliness:
Data warehouse should be user friendliness and ease to use.The DW should a common front-end across the company - based on user roles and security levels. And it should also be intuitive enough to have a minimal learning curve for most users.
Operational Efficiency:
Operational efficiency can be achieved only with a DW design that is easy to implement and maintain. A technically solution might be beautiful, but a practical, easy-to-maintain solution can give better results in the long run. Data warehouse should be easy to support to business change requests. Errors and exceptions should also be easy to remedy, and support costs should be moderate over the life of the DW.
IT Principles
Scalability:
Scalability is often a big problem with DW design. The solution is to build in scalability from the start. Choose toolsets and platforms that support future expansions of data volumes and types as well as changing business requirements.
Compliance with IT Standards:
DW design should compliance with IT standards and can take advantage of skill sets of IT and business users.


These principles, can help in a better position to recognize and address potential problems before they turn into project killers but won't guarantee we will always achieve our desired results in designing and implementing DW.