Working with data governance in Azure

Data governance refers to the overall management and control of an organization’s data assets. It involves establishing processes, policies, and guidelines to ensure availability, integrity, security, privacy, and the effective and efficient use of information. This is always important, but it is especially crucial when we’re talking about ML, as ML models are based on data. Whether we’re talking about data used to train our models or data generated by our models, it does not change the fact that we need to be aware of every piece of information we process and what its life cycle is.

To implement data governance effectively, organizations typically need to establish a data governance framework or strategy, which outlines the structure, processes, and responsibilities for data management. This framework should include the formation of a data governance committee or council, data governance policies and procedures, data stewardship...