Path to predictive data management

Let’s continue the evolution of our data services. We discussed reactive services first, where our data team was in a position to simply react by providing necessary support for the businesses whenever a DQ issue or a data need appeared.

We’ve talked about proactive services too, and how we turned reactive into proactive, albeit with some failures and learning along the way.

We went by the twofold path, where, on one side, we analyzed what we learned from our reactive requests, and then tried to convert those reactive requests into proactive data fixes, whenever it felt viable. On the other hand, we also identified a number of very deterministic and straightforward fixes of the data itself, which we could just do fully on our own remit, following the standard definitions of DQ dimensions. So to say, there were data fixes that just needed to be done… period.

We’ve also mentioned the third direction of this, which...