Not to outshine “The Data Puppets” by Scott Taylor and company, but one could envision a horror film around data, and most notably around data governance. This comes from a common saying that “data governance is dead.” Granted, we also hear “analytics is dead,” “the United States is dead,” or my favorite of late, “AI is dead.” None of these are true, but one could envision a horror film around data. 

But the real nightmare for me is the occasional person that starts to promote the idea that “data governance is dead.” I hate that. It has been articulated by: Forbes, Malcolm Fraser on Medium, and Jason Larson, among others. 

Two years ago, my son and I took a trip to Spain and hiked the English Route of the Camino de Santiago or the Path of St. James. This is a pilgrimage hike to Santiago de Compostela in Northwest Spain. Just prior to the trip, I was at DGIQ in San Diego, where I attended a few concerning presentations of the state of data governance and saw some very troubling marketing messages by software vendors. They were positioning the idea of governance = enablement. 

As we set off from A Coruña, I saw a LinkedIn post on my phone that said “data governance is dead” with a picture of an old gravestone next to it. For the next two days, my resentment grew towards that message. I never posted on it, as when I returned home, I picked up COVID for the first time from my wife who had attended a mass transmission event back home. That is about to change. 

The resentment festered over the new few days, but I successfully put it out of my head to focus on my vacation plans. However, over the next two years, there were quite a few re-statements of the same thing. I remain committed to fight this battle the best I can, as I strongly believe that data governance is NOT dead as the following questions always come back into focus: 

  • Who is going to focus on getting the right data into the right places, with the right training, to make it available and usable for the company? This is the intersection of dataOps and data enablement. 
  • How are we going to address uncovered data quality issues when they arise? Who is going to take charge and get them fixed? 
  • What will be the process for establishing a data privacy policy, identifying privacy categorization and characteristics, and addressing audit privacy concerns as they are raised? 
  • Who will help answer questions about privacy, what data can be shared, and with whom? 
  • Who will work between data analysts, knowledge workers, and security staff (CISO) to set up access controls and provide support to data access needs to be worked by the right people? 
  • Who will partner with data engineers, data analysts, and data stewards to populate the right documents to enable knowledge workers on what data is available, critical, and trustworthy as we roll out new data capabilities or products? 
  • Who will correct frustrated data users to better data definitions, available content, and best practices to run queries and distribute data? 
  • Who will advance and support data literacy progress to expand, create, and use data with increased confidence? 
  • How will we bring people together to share needs, address risks, and share lessons learned to grow a data culture? 
  • How will we collect and act on the needs of the organization for the next big thing? 

When data governance is doing well, we find that these are the points that allow us to make a big difference. We need to bring people together, focus on the data governance function, and set our organizations up for success. 

Data governance isn’t dead. It is something we must do to be successful. We need to focus on what needs to be done, share how to do it, stay committed to execution, and promote the successes of those who are using data day in and day out. 

For more information on data governance and helping to breathe life into your data governance or data program, reach out to experts at Wavicle.

WIT Leader

Data Team

Builds secure, governed data platforms that power analytics and feed AI models with clean, real-time, and high-quality data.

View all my Posts

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