Book Image

Data Governance Handbook

By : Wendy S. Batchelder
Book Image

Data Governance Handbook

By: Wendy S. Batchelder

Overview of this book

2.5 quintillion bytes! This is the amount of data being generated every single day across the globe. As this number continues to grow, understanding and managing data becomes more complex. Data professionals know that it’s their responsibility to navigate this complexity and ensure effective governance, empowering businesses with the right data, at the right time, and with the right controls. If you are a data professional, this book will equip you with valuable guidance to conquer data governance complexities with ease. Written by a three-time chief data officer in global Fortune 500 companies, the Data Governance Handbook is an exhaustive guide to understanding data governance, its key components, and how to successfully position solutions in a way that translates into tangible business outcomes. By the end, you’ll be able to successfully pitch and gain support for your data governance program, demonstrating tangible outcomes that resonate with key stakeholders.
Table of Contents (24 chapters)
1
Part 1:Designing the Path to Trusted Data
7
Part 2:Data Governance Capabilities Deep Dive
14
Part 3:Building Trust through Value-Based Delivery
20
Part 4:Case Study

AI considerations

At the time of this writing, AI has become the topic of almost any conversation related to data. Most data practitioners, like myself, are excited about the potential that AI has to offer but also want to see governance applied to AI practices. Data professionals are in higher demand than ever due to the data governance needs to support AI. The top questions include the following:

  • How do I ensure that the underlying data set used to train AI is appropriate?
  • How are prompts protected? Are they retained?
  • How do we protect intellectual property (IP; for example, source code) if entered into an open source AI solution?
  • How is my data protected?
  • How are GenAI products being trained? What happens to the data?
  • How do we ensure that input and output are handled ethically and in accordance with our company values?

There is so much to be defined around AI, and the pace of change is only increasing. Many organizations are looking to their CDO...