Data governance

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.

Fundamentals of data governance

Let's try to understand the fundamentals of data governance:

• Accountability
• Standardization
• Transparency

Transparency ensures that all the employees within an organization and outside the organization understand their role when interacting with the data that is related to the organization. This will ensure the following things:

• Building trust
• Avoiding surprises

Accountability makes sure that teams and employees who have access to data describe what they can do and cannot do with the data.

Standardization deals with how the data is properly labeled, describe, and categorized. One example is how to generate email address to the employees within the organization. One way is to use [email protected], or any other combination of these. This will ensure that everyone who has access to these email address understands which one is first and which one is last, without anybody explaining those in person.

Standardization improves the quality of data and brings order to multiple data dimensions.