7 things you should keep in mind when designing a data warehouse


Data design

Enterprise data warehouses (also known simply as data warehouses) are similar to what existed before we had computers, when there were central filing systems. These filing systems of yesteryear got information from several sources ensured that this was properly managed for efficient storage as well as retrieval, and delivered information to several sources for the purpose of analysis. Now these systems helped reduce data duplication and to a large extent did eliminate problems with regard to finding lost files.

Yes, in a similar way, enterprise data warehouses are very much like central filing systems. It is a central data respiratory that is made by combining data from one or more different sources. These warehouses store historical data as well as current ones and use them in creating trending reports for reporting to senior management such as quarterly and annual comparisons. And, data that are stored in warehouses are uploaded from operational systems like sales, marketing, etc.

However, as it is with every technology, there is a need for data warehouses to be designed, implemented as well as properly maintained for them to live up to their billing. And, it is in this regard that the following seven principles of effective data warehouse design are discussed. They consist of both business as well as IT principles.

Business principles

Organization-wide consensus

At the very onset of deploying data warehousing, there is the need for a consensus-building process, which assists in guiding the planning process as well as the design plus implementation process. So if your workers as well as managers see data warehousing as unnecessary they will not use it as they ought to or worse still see it as a threat to their jobs and so will not use it at all. Therefore, make early effort to include all stakeholders and gain their acceptance regarding data warehousing before it is implemented.

Data integrity

Data integrity is crucial to your success with enterprise data warehousing. Consequently, any design should start by reducing the possibility of data replication as well as inconsistency. Also, data integration plus standardization should equally be promoted.

Implementation efficiency

In order to assist in meeting the needs of your company as early as this is possible and help reduce project costs, data warehouse design ought to be straightforward plus efficient to carry out. In other words, designing a technically robust data warehouse without giving any consideration to the difficulty or implementation of such design is counter-productive. Instead, you should go for simplicity.

Operational efficiency

Operational efficiency is actually a corollary principle to that of implementation efficiency. After being implemented, data warehouses ought to be easy to support. They should equally ensure rapid responses as far as business change requests are concerned. In addition to this, it should also be easy to correct errors and even exceptions.

User friendliness

Even though issues regarding user friendliness as well as ease of use are resolved by technical people they remain business issues. This is because if the people who make use of data warehouse find this difficult to use, then there is a business end-user problem.

IT principles

IT standard compliance

Compliance to information technology standards is probably the most important of the IT principles. Therefore, conforming to existing information technology standards to ensure that tool-sets plus platforms chosen to implement data warehouse agree with this standard is key.


This is usually a huge problem with data warehouse design. In order to resolve this, from the very onset scalability should be factored in. Consequently, platforms and tool-sets, which support data volume expansions in the future, should be chosen.



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