3 Aspects of a Data Governance Benchmark
- by 7wData
Laggard? Leader? Ammo for business case? Changes in approach or strategy? Whatever the reason, people want benchmarks and we get asked about them all the time. I think its probably because a data governance benchmark is an important touchstone on the governance journey that provides people with perspective and confidence that says ‘you’re not alone, crazy or both.’
As the market leading data governance platform with more implementations across an array of industries than all competitors combined, Collibra is in a unique position to do something about this. We have a critical mass of data sources that we can use to begin to craft and provide a meaningful benchmarks that can be used to provide guidance for our customers. So it will come as no surprise that we are working on exactly that.
What do you measure? The word benchmark is a loaded term and one which is probably a good candidate to be governed itself. What, exactly, should be benchmarked? The one universal assumption is ‘companies like mine,’ but we all know that is like snowflakes, with no two being the same. Our perspective is to use three broad categories: Counts, Adoption, and Acceleration.
How do you measure? With a classification of counts and measures defined, how exactly do we go about measuring them? The first challenge is gathering the data. It would be great if we could simply send out a survey and have everyone respond, but that is not realistic. To do this right, we need details at reoccurring frequency that no one will have time to provide. Enter the cloud and an integration effort. With the majority of our customers either already on or moving to a cloud implementation, a lot of usage data can simply be queried from each customer instance and stored anonymously. Unfortunately, that is not where the challenge ends. Adoption data must also be collected from our support system, learning management system, and community system, and then associated to the master account and usage data. Our plan is to design a data governance benchmark data mart and populate it on a nightly basis.
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