Data warehousing is now approaching maturity in the industry. At least that seems to be the current consensus. The benefits of integrated, time variant corporate data are readily apparent. Yet, few organizations really appreciate how this technology will impact them in terms of time, cost and commitment in delivering business intelligence solutions. Even more surprising, a number of businesses still think of data warehouses as repositories of centralized operational data. In the majority of cases, one of two conditions exists:

  • The data warehouse resolves data management issues by becoming the integrator of operational data to facilitate cross lines of business systems processing (the defunct "subject-area database concept"), and/or
  • The data warehouse addresses both line of business as well as cross lines of business operational systems reporting.

Lesson Number One:

Understand where your organization is in terms of information processing maturity (from both an IT and business-user perspective) before taking the plunge into leading-edge data warehousing technology.

In today's world, knowledge delivery is essential. To stay competitive in the global marketplace means utilizing all the assets of the organization to optimum effect. Knowledge about the business, and our position within our respective market segment across time and within the proper business context, remains an essential ingredient to this success. If we know what we do well and how efficiently we perform within our market segment, we are better able to anticipate the future. The benefits of data warehousing as a monitor/predictor/enabler of this process are self-evident. Yet few organizations are able to operate their data warehousing environments at this level. Why does this situation still persist today, after years of exposure to data warehousing?

Let's start with our customers, the knowledge workers within our respective organizations. For decades they have placed increasing demands for more timely, accurate, on-demand information with their respective IT organizations. Data warehousing seemed to offer all the answers. For business users, it allowed them to access their data when and where required. For IT professionals, it provided the necessary breathing space to adopt and integrate the next generation of operational processing technology. Unfortunately, in most cases, this scenario never develops. The knowledge workers usually require a lot more help than we thought in being able to cope with the latest technology. This situation is a result of not only the challenge of new software tools but, more importantly, new ways of doing business. In addition, the data itself proves to be a considerable challenge as, for the first time, data from multiple systems must be synchronized on a regular basis. IT organizations find themselves plowing into largely uncharted waters at this point as they try to cope with the problems and issues arising out of data-centric processing. Technology on its own does not provide a solution, since this is primarily a business issue. Daunted by the considerable data integration challenge, IT departments fall back on old habits of building application-bound data marts, thereby laying the foundation for future failure.

Lesson Number Two:

Avoid building a problem for the future by accepting the lure of a "quick fix" data mart solution without a forward-looking architectural foundation.

Our final challenge involves generating the necessary sponsorship and business commitment. Again, in the majority of cases, most data warehousing efforts fail because the sponsorship chain usually resides within the IT organization instead of the business community. The attraction of adopting the latest technology is hard to resist. Information systems departments propose huge technology investments with an incomplete understanding of where the true value propositions exist. In many instances, these departments lack the political will to address the lack of data integration within the organization's business systems. This situation results from decades of stovepipe business solutions. These habits are extremely difficult to break, since progress often requires a cultural change in the business. Faced with the challenge of data sharing, cultural change and new technology, committed corporate sponsorship becomes a key ingredient to success.

Lesson Number Three:

Ensure that your data warehousing initiative has the necessary and visible business sponsorship, supported by a realistic business case, prior to initiating any significant technology investment.

To avoid repeating these three hard lessons in data warehousing requires an ongoing commitment to:

  • Building the necessary infrastructure which will continually promote/educate the concept to the business community prior to launching a data warehousing program.
  • Conducting a current state assessment of both IT and the business community in terms of their current level of information processing maturity. If the business is still trying to cope with day-to-day operational activities, then clearly it is not ready for decision support and data mining.
  • Adopting a "business first" approach to the development of realistic value propositions prior to delving into the myriad of data warehousing technology. This can be accomplished by utilizing industry specialists who understand the business processes and best practices for recognizing and qualifying requirements for business intelligence. Once understood, a more selective and accurate assessment of the available technology can be made.
  • Developing a commitment within the organization to a data stewardship program. These business-content experts will establish the "rules of the road" for corporate data structures and act as data auditors of the process. Their link to IT is through a data administration function which can establish the "system of record" for the dimensions of the data warehouse (thereby initiating the data quality and data reengineering process).
  • Time boxing delivery in support of the value propositions and data warehouse architecture to short, well-defined increments while avoiding the lure of leading-edge technology.

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