9 common data governance mistakes and how to avoid them

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When companies are looking to upgrade and improve their data infrastructure, one of the most important elements has nothing to do with hardware or software. Instead, data governance is likely to determine the success of any effort.

Simply put, a strong data governance program has clear rules and guidelines for how data should be created or collected, stored, protected, accessed, used, and shared. It is as much about human activity as it is about technological processes.

To this end, Nicola Askham advises organizations on how best to integrate data governance into their practices, in order to better understand and manage this data. Askham goes by the eponymous position of "The Data Governance Coach" for the consultative practice.

For nearly two decades, Askham has helped organizations reduce costs and inefficiencies and stay competitive by better understanding data governance principles.

"People usually come to me because their data is in a mess and they need help sorting it out, or because they realize they're investing money in new initiatives that fail due to poor quality data," Askham told VentureBeat. "In addition to offering coaching and consulting to help my clients better manage their data, I host my popular training courses. I think it's important to give people the skills to make sure data is used to solve problems and make more informed decisions."

The most overlooked element in most data governance programs is the human element, Askham believes.

"Culture change is critical to the success of a data governance initiative. In fact, I would go so far as to say that in the early stages, it's more about people than data," said Askham: "It's vital that you achieve this mindset shift. All business users in your organization need to understand that data is an asset and manage it as such. Design and implement a data governance framework without dealing with the human side will spell disaster."

That said, the questions Askham says he asks most often relate to the "ownership" of data

"I get the most questions about data ownership topics: what data owners should do, who should be the data owners, how to engage them, etc." Askham said.< /p>

To aid in these efforts, Askham has published a guide detailing “The 9 Biggest Mistakes Companies Make When Implementing Data Governance.” Briefly, the errors described in his report include the following:

Mistake 1: Initiative is IT-led

“The key to data governance success is getting stakeholders to take ownership of their data and take the lead in data governance initiatives,” Askham wrote in his report, published last year. . "When I do a data governance health check for companies that are having issues, it's quite common for IT to lead the data governance initiative."

To avoid this problem, the organization must recognize the need to take ownership of its data and support the data governance initiative, according to the report.

Mistake 2: Not understanding the maturity of the organization

"Ultimately, until your organization is able to think about data in the right way, a large-scale data governance initiative is likely to fail because the necessary communication and education will be confused or fall on deaf ears," Askham wrote.

There are two steps to avoid this problem, according to Askham's report. The first is to assess your current level of data governance maturity. The second is to be clear about what you hope to accomplish with data governance.

"This will ensure that everyone involved in your initiative clearly understands what the initiative is trying to accomplish and how it will positively impact their part of the organization, which...