There’s a lot of confusion in the business world about what “data governance” actually means. The fact that it’s often (incorrectly) used interchangeably with the phrase “data management” only further muddles understandings. But while these concepts are related, each refers to a different, albeit critical, part of using your data as effectively as possible.
Let’s clear up some of the confusion so you can think more carefully about what good data governance is, and how it can help your organization.
What Is Data Governance?
When we talk about data governance, we mean all the people, processes, policies, technologies, and systems that collectively ensure your organization uses data effectively. You can see why things might get confusing—that definition covers a lot of ground. But the ultimate goal of data governance is to make sure your data is managed, protected, and reliable.
Without good data governance in place, you run some pretty big risks. For one thing, your organization may wind up using information that is incomplete, inaccurate, or unsecured. Your data may also become less accessible, making it more difficult for users to complete tasks efficiently. And without proper policies in place, your users may all do things a little bit differently, leaving your data much less secure and your information less trustworthy.
The net effect of these risks is an organization that’s slower, more prone to error, and less able to understand the market it serves. Those characteristics aren’t on anyone’s quarterly goal sheet.
How Is Data Governance Different from Data Management?
If you’ve spent any time learning about data management, then some of the risks outlined above may sound very familiar. After all, bad data management can also lead to issues of incomplete or inaccurate information.
But although the two concepts are interrelated, data management is really just one aspect of data governance. Data management is chiefly concerned with breaking down data silos, improving data accuracy, and securing information against errors; data governance includes all that plus your people, technology, systems, and policies.
Here’s a more concrete example. Say your organization collects customer addresses. Data management ensures that those addresses are accurate, recorded in a consistent format, and that the information is complete.
Data governance includes all of that, too but takes things a few steps further. It determines who has access to those addresses and how, what technologies and systems are used to house and retrieve them, and what policies are put into place to help prevent errors and avoid the misuse of that data.
In other words, if data management is about making sure the data is good, data governance is the overall body of practices that ensures your data is also used well and ethically.
How Do You Put Data Governance into Practice?
Given the scale of what data governance actually requires, it may not surprise you that most organizations rely on a whole team of people to put it into practice. That might include key business executives, your IT team, your end users, and a data governance committee to develop key policies.
If that still sounds like a lot to bite off and chew, that’s okay. It’s probably just a sign you need to find the right partner to help you get started. Then you can begin to develop a data governance plan that provides the best possible foundation for your business—now and as you grow.
Resultant has structured our Govern by Design methodology to be that overarching system of data governance, holistically protecting your organization’s data and aligning with your strategic goals.
Get a grip on your data and make better decisions. Find out how
Originally published April 18, 2022. Updated July 16, 2024
