I. INTRODUCTION We begin this article using the words of John Edwards 9, who is a veteran business technology journalist with several business and technology publications, who says: “Today, every data transaction is a business transaction. That’s why it’s vital to build a data governance framework that is strong, secure, adaptable, and as error-free as possible. A critical mistake many IT leaders make is introducing data governance policies without ensuring that all important parts of the company have the tools and knowledge to implement them effectively.” Data Governance (GD) has been a difficult area of business to work in. When everything is working and no noise is causing problems, your efforts go unnoticed. On the other hand, when problems arise and things go wrong, data governance is the first area to blame — processes don’t work, and you are not controlling it correctly! Therefore, to demonstrate to shareholders 2 that the effort and investment made in GD are benefiting the business, reducing costs, and increasing revenue, it will be necessary to implement some metrics. This will allow the company to understand and see the improvement that is occurring. But where to start and what to measure? To do so, we need to define ‘Data Governance Metrics’. In other words, we try to say something based on the determination of its uniqueness and describe what is specific and distinct about metrics, their meaning and their importance. So, the question immediately arises:
Paulo Roberto da Silva Oliveira (Sat,) studied this question.