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?

Executing day-to-day data processes

In the ever-evolving landscape of data management, executing day-to-day data processes is akin to navigating a complex and dynamic ecosystem. At the heart of this ecosystem is change management, a critical component that ensures data processes are adaptable and responsive to the shifting demands of business and technology. Embracing change management is not only about implementing new systems or protocols but also about cultivating a mindset that is ready to accommodate and leverage change for better data outcomes. Simultaneously, handling data process modifications with agility and precision is paramount. It involves a keen understanding of the nuances of existing procedures and the foresight to anticipate the impact of changes.

Here are some of the best practices for change management in the data process:

  • Impact analysis: Before making any changes, perform a thorough impact analysis to understand the repercussions across various facets...