"Bonuses" from a DW project
By the way, there are a number of "bonuses", which you gain as you go:
  • You learn a lot during the process
  • You get business routines adjusted
  • You improve quality (of processes and data)
  • You speak a consistent business language across the organisation (and follow the same rules)
  • You understand the business better ("Aha!" experiences)
  • You see new patterns of causation
  • You find the real pains

This is so important that I have also written a book about it:

Design Thinking Business Analysis - Business Concept Mapping Applied
Thomas Frisendal
© Springer, 2012
ISBN 978-3-642-32843-5



Data Warehouse Challenges

Even though Data Warehouse must be considered mainstream, there are still some mistakes, one can make...
I have tried to list the major ones here.

Information-driven Analysis

One of the key things to do, if you want to ensure a success, is to spend the time necessary on understanding and documenting the business and its needs. The most important activity is the modelling of the business concepts.
Data Warehouse is information-driven, which is why concept mapping is driving the whole of the rest of the project.
Experience from quite a few projects have shown that the better the business model is, the shorter and cheaper the implementation project will be. The reasons for this are many: Avoid misunderstandings, no scrap and rework, deliver to the needs, talk the right language, intuitive solutions, happy users in the end - and more!
In short, this is called Information-driven Business Analysis, and you can learn more from our eLearning offerings.

Sponsorship

Many see Data Warehouse as a technical (IT) project. IT IS NOT! What it is is: Business Development!
Successful Data Warehouse projects are:
  • Aligned with the Strategy of the Business
  • Aligned with Business Plan
  • Adress key Business Needs
  • Sponsored by Top Management
  • Owned (by someone in the top of the organisation)
  • Focused on Data Quality challenges and solutions from the very beginning
  • Closely followed by the Owner and the management group
  • Are resolved by way of management intervention when problems arise
If you understand and follow those "simple" principles, you will get the results, the business needs, with high quality and on schedule. See the analysis and design page for more information about the early phases and the Business Concept Mapping page for information about the business mapping itself. Happy DW implementation!
You might also enjoy my latest book:
GraphDataModelingFrontPageReduced

Data Quality

One very big - but very common - mistake is underestimation of the impact of data quality. It is probably the no 1 showstopper in the Data Warehouse world. See our Data Quality page for more information.

Data Governance and Master Data

Many organisations do not invest in these disciplines. Maybe because they do not understand what they really are. They are: Asset management. Simple as that. Information is one of your most important assets and should be on our balance sheet. Think about the impact of losing all or even half of your data overnight...
So Data Governance really puts in place some Information Owners and some "Information Controllers". Master Data Management does to your shared data (such as customers, products and so forth) what standard schedules of accounts, standard costcenter structures and standard bookkeeping dimensions do for your financial assets. Why is it that many companies do not treat information as an asset? Beats me, honestly.
One of the issues being you have to scrap and rework business concept models.