Preface

In an age where data is often heralded as the new oil, the role of a data steward has become increasingly critical. As organizations navigate the complexities of digital transformation, the need for a comprehensive understanding of data stewardship is more pressing than ever. This book is a response to that need—a guide that demystifies the role of data stewards, equips aspiring professionals with actionable insights, and serves as a beacon for those who wish to master the art and science of data management.

The journey of writing this book began with a simple observation: while there is a wealth of information on data science, engineering, and analytics, there is a noticeable gap when it comes to the nuanced field of data stewardship. This gap is not just academic; it reflects a real-world disconnect that organizations grapple with daily. The role of a data steward is often misunderstood, undervalued, and yet, absolutely vital to the health and success of any data-driven enterprise.

This book aims to bridge that gap by providing a comprehensive and practical guide to the world of data stewardship. It is crafted for individuals who recognize the importance of data as a strategic asset and are seeking to either step into the role of a data steward or enhance their existing data management practices.

As you turn these pages, you will embark on a journey that begins with the alignment of business strategy to data strategy and culminates in the implementation of robust data stewardship programs. You will learn not just the theory but also the practicalities of managing data effectively. Each chapter is designed to be both informative and engaging, offering real-life examples, case studies, and best practices that have been tested and proven in the field. Moreover, this book recognizes the ever-evolving nature of technology. It delves into how emerging tools such as Generative Pre-trained Transformer (GPT) models can revolutionize data governance and stewardship, providing a glimpse into the future of data management.

The preface would be incomplete without acknowledging the collective wisdom that has shaped this book. Insights from industry experts, feedback from peers, and the experiences of those on the front lines of data stewardship have all contributed to its creation. This book is a testament to the power of collaboration and the shared vision of elevating the practice of data stewardship.

Who this book is for

This book is for individuals interested in the role of a data steward and seeking to advance in the field of data management. It targets existing data team members, chief data officers, chief digital officers, strategy managers, and newcomers to the field aiming to gain a deeper understanding of data stewardship responsibilities, best practices, and implementation strategies.

What this book covers

Chapter 1, From Business Strategy to Data Strategy to Data Stewardship, explores the transformation from business strategy to data strategy and, ultimately, to data stewardship, emphasizing skill development and execution practices for effective data management programs.

Chapter 2, How Data Stewardship Can Help Your Organization, explains data stewardship’s role in enhancing competitive advantage by improving data accuracy, security, and management, leading to cost reduction and increased customer satisfaction.

Chapter 3, Getting Started with the Data Stewardship Program, guides you on starting a data stewardship program, highlighting stakeholder buy-in, key program elements, and strategies for addressing initial data management challenges.

Chapter 4, Developing a Comprehensive Data Management Strategy, takes you through creating a data management strategy, from assessing current states to defining future goals and executing governance, quality, and security plans.

Chapter 5, People, Process, Technology, delves into the interplay of people, processes, and technology in data stewardship, showing ROI and improving practices through automation and artificial intelligence (AI).

Chapter 6, Establishing a Data Governance Structure, outlines the steps for establishing a data governance structure, fostering a data culture, and defining KPIs, and provides tools for creating and measuring a successful governance program.

Chapter 7, Data Steward Roles and Responsibilities, defines data steward roles, emphasizing data quality, access control, security, and compliance, equipping you with frameworks for effective data governance.

Chapter 8, Effective Data Stewardship, discusses principles of effective data stewardship, including data ownership, role assignment, accountability, and leveraging continuous training for a successful data governance roadmap.

Chapter 9, Supercharge Data Governance and Stewardship with GPT, explores using GPT for enhancing data governance and stewardship, automating management tasks, and ensuring data privacy, security, and the prevention of bias in AI applications.

Chapter 10, Data Stewardship Best Practices, shares best practices for data stewardship, aligning mindsets, upskilling teams, fostering accountability, and ownership, and integrating emerging technologies for effective data management programs.

Chapter 11, Theory versus Real Life, addresses the gap between theory and real-life data stewardship, emphasizing collaboration, continuous monitoring, and improvement for bridging this divide and ensuring program success.

Chapter 12, Case Studies, presents two case studies on effective data stewardship: the Bank of East Asia fosters a data-driven culture for operational efficiency, while Fencore’s solution streamlines fund management, showcasing the practical impact of data strategies.

To get the most out of this book

We assume you have a basic understanding of data life cycle and process flow management in the context of enterprises. You should also be familiar with the basic data and cloud technology for data ingestion, transformation, and storage. Ideally, you should have experience in fostering a new working culture for an organization and a strong interest in extracting the utmost value from raw data.

To fully engage with the practical elements of this book, especially in chapters discussing the integration of AI in data stewardship, you may need to set up an OpenAI/Azure OpenAI account for access to GPT models.

Additionally, while not mandatory, registering with professional bodies such as the EDM Council (EDMC) or DAMA International could enhance your understanding and provide valuable resources aligned with the advanced topics covered in this book. These platforms offer a wealth of knowledge and community support that can complement your learning journey.

Conventions used

There are a number of text conventions used throughout this book.

Keyword: This indicates a new word or phrase when it is first introduced. Here is an example: “Data stewardship is the practice of managing data ethically and responsibly.”

Italics: This is used to add emphasis to a sentence or add a figure, table, chapter, or other reference. Here is an example: “We have several key building blocks, as illustrated in Figure 2.2 in Chapter 2.”

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