Book Image

Data Stewardship in Action

By : Pui Shing Lee
Book Image

Data Stewardship in Action

By: Pui Shing Lee

Overview of this book

In the competitive data-centric world, mastering data stewardship is not just a requirement—it's the key to organizational success. Unlock strategic excellence with Data Stewardship in Action, your guide to exploring the intricacies of data stewardship and its implementation for maximum efficiency. From business strategy to data strategy, and then to data stewardship, this book shows you how to strategically deploy your workforce, processes, and technology for efficient data processing. You’ll gain mastery over the fundamentals of data stewardship, from understanding the different roles and responsibilities to implementing best practices for data governance. You’ll elevate your data management skills by exploring the technologies and tools for effective data handling. As you progress through the chapters, you’ll realize that this book not only helps you develop the foundational skills to become a successful data steward but also introduces innovative approaches, including leveraging AI and GPT, for enhanced data stewardship. By the end of this book, you’ll be able to build a robust data governance framework by developing policies and procedures, establishing a dedicated data governance team, and creating a data governance roadmap that ensures your organization thrives in the dynamic landscape of data management.
Table of Contents (18 chapters)
Free Chapter
1
Part 1:Why Data Stewardship and Why Me?
5
Part 2:How to Become a Data Steward and Shine!
12
Part 3:What Makes Data Stewardship a Sustainable Success?

Assessing data maturity

Data maturity refers to the extent to which an organization can effectively and efficiently utilize its data. It encapsulates several facets, including data management, data governance, data quality, data integration, and the ability to derive insights and value from data. There are some well-recognized data maturity frameworks from the Enterprise Data Management Council (EDMC) (https://edmcouncil.org/) and Data Management Association (DAMA) (https://www.dama.org/).

You can refer to Figure 4.5 in Chapter 4, Developing a Comprehensive Data Management Strategy, for the gap analysis of data maturity.

When you want to show the gap between the current and target state to the stakeholder, and when you want to keep track of the improvement in data maturity level for the organization, you need to know where you are now. That is why you need to have a data health check via a maturity assessment.

Why is a data maturity assessment vital to your organization? Here...