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Home Data Architecture Data Governance Challenges

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Data Governance Challenges

Jim McHugh
April 18, 2023
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graphic of coder working with data fiefdoms of locked and unlocked files over a photo of hands on a keyboard
Many people and companies talk about data governance, but very few execute a well-thought-out data governance program. So why is there such a disparity between what we want and how we implement data governance?

Data Fiefdoms

The major challenge in executing a successful data governance program is the existence of a data fiefdom. A data fiefdom is a business unit (or individual) unwilling to share its data with other organization members. They feel that they will be exposed by the lack of maintenance and general dirtiness of their data. These individuals understand that data is power, and if they share their data, they will lose control of their area of expertise, become redundant, and possibly lose their job.

The resolution to this data fiefdom challenge is C-Level sponsorship (and understanding). Data governance is a strategic priority, and all employees must understand that non-compliance with the data governance program is unacceptable. Therefore, this requires more than a single email stating that data governance is a priority. It requires a continued and unwavering commitment to the program’s success, knowing there will be challenges along the way.

Data Quality

As mentioned above, dirty data exists in almost every OLTP system. Fields that should have been required were not constrained appropriately, or additional data is needed, but capturing that data was not prioritized. This happens to all applications as they mature and revealing these issues should be seen as an opportunity. Exposing the data challenge allows it to be appropriately prioritized against other strategic needs.

Unfortunately, these fears, like most fears, are worse in one’s mind than in reality. Every system has dirty data. Over the years, I have seen individuals use comment fields as “smart data repositories” where the users entered a code to enhance the data because it would take too long or cost too much to add a new field to the data structure.

Expertise

Data governance is a process, and not every organization is equipped to implement this type of rigorous program. This is where the organization’s strategic leaders need to understand their team’s limits and the value of establishing this expertise in-house. Yes, this will cause an initial investment in establishing the data governance team. However, this investment should reap the rewards of increased sales and market share that will exceed the initial investment.

In conclusion, data governance is critical to the success of an organization. Consequently, it is the responsibility of the senior leaders to not only implement the data governance program but they need to monitor and promote the data governance program continually.

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