The deception in our case is the accuracy of the data and the return on investment of the data warehouse solution. Too often projects make compromises in the implementation of a business intelligence solution that create massive cost and user dis-satisfaction downstream that lead to the failure of BI projects:
* In the project management setting un-realistic or un-deliverable targets, opting for tactical solutions that soon overtake the main project and the failure to communicate issues to senior management and business users that will affect the delivery timescales and costs.
* In the requirements phase believing that you know better that the user and not getting their sign off that they understand and agree with the requirements.
* In the analysis phase the failure to correctly identify the master sources of information and to do sufficient work to understand how the data is stored in the source system and what data is needed to meet the requirements.
* In the design phase the expediency of allowing the developers to ‘get on with their job’ by not thoroughly validating the design and checking the sources to ensure that the design meets criteria such as timeliness, reliability and accuracy.
* In the build phase by coding to the bear minimum to get the job done and not to a standard that ensures it will run successfully time after time.
* In the testing phase where as well as the standard data and volume data you test all the data boundary conditions that might occur.
* In the data quality aspects of the programme where data is fixed on the way in to the system or after it has been loaded because it is ‘too difficult’ to fix it back at the source system.
These are only a few examples but each of them makes the final solution more difficult (a tangled web) and therefore more costly to operate and maintain. If you are in a project where doing the right thing is compromised then remember that the project will have to pay for these ‘efficiencies’ later. Project managers should always strive to improve any project lifecycle and deliver on time. Too often, however, it becomes expedient to bury the truth and deliver anything to meet an arbitrary date that, in the long term, leaves the business user unsatisfied.
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This article was originally published on BIonRails, another Data Management & Warehousing website