Should You Build BI Before You Clean Your Data?

Implementing a business intelligence environment against data you don't trust?  Sounds counter-intuitive, some would say: ‘just plain wrong.'  How could you possibly build a data warehouse and cubes on data that might not be accurate?  You shouldn't of course, and that is 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 your company has an urgent need to manage to 3 or 4 KPI's around inventory, the 6 months that it might take to understand your inventory data and make sure it is correct is a very long time.

But there is an even bigger risk.  Think about how you find out that you have bad data.  It is almost never by putting data into a system.  You only find out about bad data when you try to get data out.  So this begs the question - if you are going to embark on a data governance 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?

Nothing highlights inconsistencies in your data like trying to build a dashboard against it.  Nothing will focus data governance and cleaning efforts like clearly understanding the numbers you need to drive your business.  Not just the numbers themselves, but what are the components of those numbers?  What were the transactions that placed those numbers into ...