Today’s businesses run on data. It’s essential for any corporation to look for insights about their customers based on the data they collect. That collected information drives everything from business strategy to customer service.
In order to retrieve insights from the massive amounts of data they collect, companies are turning to machine learning, and for those of us concerned with governance, this has begun to create difficult new challenges for the ways we think about and govern data within the enterprise.
Analysts have traditionally used domain knowledge and human expertise to develop models of how their consumers interact with their business. They use data to verify and track the accuracy of these models, which typically are combinations of simple aggregate values (like age, group, and region) and somewhat limited by their generalities.