Having very large volumes of data is not enough to make very good decisions that have a positive impact on the success of a business. It's very important to make sure that only quality data should be collected, preserved, and maintained. The data collection process also goes through evolution as new types of data are required to be collected. During this process, we might break a few interfaces that read from the previous generation of data. Without having a well-defined process and people, handling data becomes a big challenge for all sizes of organization.
To excel in managing data, we should consider the following qualities:
- Good policies and processes
- Accountability
- Formal decision structures
- Enforcement of rules in management
The implementation of these types of qualities is called data governance. At a high level, we'll define data governance as data that is managed well. This definition also helps us to clarify that data management and data governance are not the same thing. Managing data is concerned with the use of data to make good business decisions and ultimately run organizations. Data governance is concerned with the degree to which we use disciplined behavior across our entire organization in how we manage that data.
It's an important distinction. So what's the bottom line? Most organizations manage data, but far fewer govern those management techniques well.
