What is the #1 data governance myth you have had to dispel or are working on dispelling at your organization?

“Data governance stifles innovation and speed at which we can build AI solutions”. Educating stakeholders and data science teams on the long term impact (and measuring it) of data governance on sustainability of AI and rest of data analytics maturity is critical.

The #1 myth of data governance is that your business stakeholders need to care about data governance. They don't, and arguably shouldn't.  Your customers should be razor focused on supporting their customers, and data is simply an enabling capability to that end.  If we can overcome the myth that we need to make businesses care about data through misguided efforts like 'data literacy', we can focus on pivoting data governance to the enablement function that it needs to become.  The first step at this pivot is quantifying the business benefits of better governance.     

I believe our primary challenge revolves around the misconception that technology alone can resolve all issues related to data quality and management. This is particularly evident in the healthcare sector, where data is often of poor quality. Many hold the belief that technology can rectify poor data quality, instead of focusing on the importance of initially acquiring accurate and reliable data. Additionally, there is a widespread notion in healthcare that data collection is straightforward. This belief ties into my earlier point about the perceived simplicity brought by technology in data acquisition. However, what often goes unrecognized is the extensive backend curation and validation required to ensure the cleanliness and usability of the data.

Completely agree with Chris on the "it's not an IT issue." The way I see that manifest is that everyone thinks Data Governance is a great idea for someone else to do because they'll tell me that their tam doesn't have the time, skillset... to do the work effectively.  We're spending a lot of time having discussions about right sizing the level of effort.

So on the face of it - I am going to list 2, but in reality they are the same myth represented in 2 different ways - fairly obvious to data professionals but still seen this way in a lot of big organsiations
"Data Governance is an IT issue or that Technology can solve Data Governance/Quality issues" 

If we could completely dispel this myth and get the "whole organisation" to understand, and more importantly agree,  that Data Governance is a people and process function and should be a core consideration in the design and execution of our end-to-end processes then i think we would have much more success in getting these initiatives to deliver increased value