If data isn’t managed well, your organization could be at significant Risk. This list will help you spot areas where your data governance may fall short.

One thing we all can agree on is that hindsight makes things much more clear. When we’re discussing and reviewing past issues in technology systems and failed projects, we can usually make a data path to the problem. data governance issues can exist in organizations of any size, but if you don’t know much about data governance, that’s an indication of a potential issue.

Especially as company data sprawls and grows more complex, there is a growing global initiative to get data governance and management under control, regardless of data size or profile. I came up with this list of 10 indications that you may have a data governance issue; with this knowledge of common data governance problems, you can hedge off many data issues in your organization!

When it comes to data and its access, pockets of adoption may not cut it. If you hear this type of conversation, keep in mind that it takes only one problem spot to cause a data handling issue. Adopting data governance has to include the entire cycle and scope of the organization. The reality is that it takes just one system to improperly handle a piece of sensitive data and cause an issue.

The notion of a data dictionary is usually implemented on database systems and enterprise applications. But with as many systems as are involved in today’s complex web of IT systems, it becomes a priority to ensure that all data dictionaries and business glossaries are the same. How often have you been in a situation where a field or term in one department is not the same as in another department? That’s a different issue, but the principle is the same: It’s a good idea to have one data dictionary for the organization and ensure that applications and their data profiles are modeled around that dictionary for data standardization.

If you can’t answer the question of which person or group is in charge of data administration for both definitions and data quality management, that’s a sign of a data governance issue. The data steward isn’t usually the person or group that purchases the hardware or does the backups but is the one in charge of making sure the right data is presented in the right places, the data is correct, and its lifecycle is managed correctly. Part of the lifecycle includes data archiving and eventual deletion. Who addresses these topics in your organization? Make sure you have at least one data steward with clearly delineated roles and responsibilities.

Somewhat the opposite of the point above, it is altogether possible that two groups are staking claim to the role of a data steward. While this is more of an organizational problem, it may increase the Risk of things falling through the cracks or being incorrectly governed if roles are not clearly defined. This can be especially problematic in a data deletion situation, where one group needs the data and another group doesn’t need it. Multiple data stewards can coexist but only if they are each responsible for clearly-defined projects, data sets, and/or data use cases.

Interoperable systems play a big part in our application and infrastructure profiles today.