top of page
Untitled design-20.png

an executive guide       
to data governance


This guide summarizes all the information we have in our blog. We are actively building this content. On this page, you will find clear and concise information. 

Should you require more information on the subtopic you are reading, simply click on any link to read the blog post which goes into more details.

Content of this guide

Chapter 1 Why is Data Governance critical to any organization
Chapter 2 What is managed by Data Governance
Chapter 3 How can organizations enhance the way they manage Privacy
Chapter 4 Data Governance as a way to create value
Chapter 5 How to create a Data Strategy
Chapter 6 AI Governance and reducing Data Risks
Chapter 7 The future of Data Governance
Screen Shot 2020-10-20 at 10.47.58

Download the eBook in PDF format

While we are still building out this page, our eBook is already complete. Download it today!


Let's clarify what Data Governance is and what it covers.

What is Data Governance?

There are many definitions of Data Governance. We like the one from David Plotkin (2013):

Data Governance is the exercise of decision making and authority for data-related matters. It’s a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.

The key thing to take away from this definition is that the practice of Data Governance has more to do with establishing the roles and responsibilities about how people manage and make decisions about data than about the data itself. That is, Data Governance–and Data Stewardship–is all about making sure that people are properly organized and do the right things to make their data understood, trusted, of high quality, and, ultimately, suitable and usable for the enterprise’s purposes.

What do we govern, exactly?

There are nine (9) aspects we manage with Data Governance. They are:

  1. Privacy

  2. Security

  3. Compliance

  4. Integration

  5. Data quality

  6. Metadata

  7. Retention

  8. Data risks

  9. Impact (or ROI)

A Data Governance program eventually can manage all these. Because of the impact they have on each other, it is important they are overseen through one, global and common framework.

Reference: InterPARES Trust

bottom of page