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Eliminating BI Failure: 4 Steps to Avoid Improper Data Governance
Accurate data is the non-negotiable cornerstone of any business intelligence effort How could you possibly build a data warehouse and cubes on data that might not be accurate? You shouldn’t…
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Eliminating BI Failure: 4 Steps to Avoid Improper Data Governance
Accurate data is the non-negotiable cornerstone of any business intelligence effort
How could you possibly build a data warehouse and cubes on data that might not be accurate? You shouldn’t of course, and that’s the point. Accurate data is the non-negotiable cornerstone of any BI effort.
But accurate data does not happen by itself. Data needs to be enthusiastically governed to a state of truth and reliability, and this is a big job. So big in fact, that attempting a global data governance initiative can cost so much time and energy as to obliterate the initiatives it was designed to support in the first place.
If you are going to embark on a data governance and cleaning initiative before you roll out BI, what exactly are you going to govern? How do you know what to fix, if you can’t see that it is broken?
In this white paper, we’ll explore some best practices gleaned from years of combined data governance experience to help you eliminate business intelligence project failure, once and for all.
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