Data Stewardship in Action

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To my beloved wife, Annie, the beacon of my life who has always been my strongest pillar of support and my ceaseless source of inspiration. Your patience and love have been the guiding lights in my journey of writing this book.

To our precious newborn baby, Lok Yan, the newest spark of joy in our lives. Your arrival has filled our hearts with immense happiness and has given me renewed strength and motivation. Every word penned in these pages is a testament to the hope and dreams we hold for you. You are the future; the future is yours.

To my cherished family, who have stood by me through thick and thin, always encouraging me, believing in me, and cheering me on. Your unwavering faith in me has been my greatest strength. I am forever grateful for your love and support.

And lastly, to my three lovely fur babies, BallBall, Brownie, and Creamy. Your purrs and cuddles have been the best stress-relievers during the most challenging times of this journey. Your feline antics have brought joy and laughter to our home, making the process of writing this book a delightful experience.

This book is a product of all the unconditional love, support, and patience that you have generously given me. I dedicate it to you all, with my deepest gratitude and love. Thank you!

In memory of BallBall

– Pui Shing Lee

Foreword

I have over 30 years of experience in the data industry, from databases to artificial intelligence, and in recent years, I established the Data Literacy Association, with the goal of empowering users to effectively utilize data and leverage its business potential in their daily work and lives. This book on data stewardship is extremely timely. As more users incorporate data into their everyday routines and data becomes an integral part of their lives, it is crucial for them to understand the significance of data stewardship and implement it within their companies.

It’s comparable to having a smart home equipped with intelligence, convenience, and personalized services. If you fail to secure the door and properly manage the security of your home devices while safeguarding your day-to-day data, disaster may strike one day. I urge you to read this book attentively and take action before it’s too late. It’s not just a book for technical and data professionals; it’s also relevant to business leaders and executives, as well as anyone who uses data in their daily lives.

I extend my gratitude to the book author, Pui Shing Lee, for investing significant effort in writing this book and spending time to distill his invaluable experiences and presenting them in an easily understandable manner. Thanks for your contribution to the world of data literacy.

Dr. Toa Charm

Founding Chairman

Data Literacy Association

Contributors

About the author

Pui Shing Lee is a visionary leader with two decades’ experience in FinTech, data, AI, and cloud across Europe, the US, and APAC. He is a cloud solution strategist (Data & AI) at Microsoft. With a passion for deriving actionable insights from data, he provides comprehensive solutions for customers’ journeys, ensuring tangible business outcomes.

Shing holds industry-leading certifications including DAMA CDMP and EDMC CDMC V1. His professional experience includes roles as chief data officer at Hang Seng Index, head of data governance at HKEX, and APAC director at IHS Markit. As the co-founder of the Data Literacy Association, Shing advocates for a culture-fit data strategy, self-service models, and automated governance on robust cloud platforms.

I want to thank the Packt team who have been very supportive. Vandita, Kirti, and Tejashwini, thanks for the coordination and guidance.

A heartfelt thank you to my friend Lance for being the reviewer; your insightful advice has elevated this book to its greatest potential.

I extend my deepest gratitude to Dr. Toa Charm for graciously writing the foreword of my book; your esteemed perspective has truly enhanced its value.

About the reviewers

Anthony A Afolabi is a principal consultant on major data management and governance engagements, with over 12 years of experience in the financial services, consulting, banking, and capital market sectors. He is deeply experienced in the implementation of design principles for banking applications, enterprise risk data architectures, and data warehouse solutions, planning, and mobilization, the execution of global programs, and operational risk management. He has been integral to the implementation of BCBS 239 at major banking groups, G-SIBs, and D-SIBs across Europe and North America, where he was responsible for both the end-to-end delivery and post-implementation assurance frameworks for the first, second, and third lines of defense.

Lance Yeung is the data governance lead at the Hong Kong Science and Technology Parks Corporation (HKSTP), where he steers organizations from various sectors towards success in the digital economy. His strategic leadership ensures robust data integrity and compliance, which are vital for innovation in industries such as banking, insurance, logistics, transportation, healthcare, hospitality, and government. Lance’s seasoned background includes impactful stints at the Hong Kong Monetary Authority (HKMA) and Hong Kong Exchanges and Clearing Limited (HKEX). This multidimensional exposure equips him with insights to craft data governance frameworks and strategies that enable businesses to navigate and excel in a data-centric global marketplace.

Table of Contents

Preface

Part 1: Why Data Stewardship and Why Me?

1

From Business Strategy to Data Strategy to Data Stewardship

Understanding the strategic, tactical, and operational value of data stewardship

Bridging the gap between data strategy and data operation

Unlocking business value with data stewardship

Understanding business strategy

Understanding data strategy

Operationalizing your data strategy via data stewardship

Exploring the mindset and skillset gap

Translating strategy into execution

Data collection

Data governance framework

Analytics and reporting tools

Tracking progress

Decoding data governance, management, and stewardship

Data stewards wear different hats

Summary

2

How Data Stewardship Can Help Your Organization

Defining data stewardship

The work scope of a data steward

Understanding the role of a data steward

Types of data stewards

Comparing strategic data stewardship with a standard operating procedure

Using business cases for storytelling and value realization

Creating a competitive edge with data stewardship

Summary

3

Getting Started with the Data Stewardship Program

Defining the origin and destination of your data stewardship program

Getting buy-in of data stewardship from stakeholders

Building a prioritization matrix

The impact-effort matrix

The RICE method

MoSCoW analysis

Comparing different prioritization matrices

Assessing data maturity

Building the foundation of your data stewardship program

Summary

Part 2: How to Become a Data Steward and Shine!

4

Developing a Comprehensive Data Management Strategy

What is a data strategy?

Assessing your current data environment for creating a data strategy – Where are you now?

Data maturity assessment

The CDMC framework

Fulfilling the business and data strategy – Where do you want to go?

Spider web diagram

Introducing the people, process, and technology – How do we get there?

Making the impact visible to your stakeholders - Feedback loop to measure and report progress

Engagement model

Summary

5

People, Process, and Technology

Empowering people for an effective data stewardship program

Roles and responsibilities

Skills and training

Stakeholder engagement

Demonstrating the return on investment (ROI) of a data stewardship program

Standardizing processes to ensure consistent data operation

Data governance framework

Data compliance and risk management

Leveraging technology to fast-track your data journey

Data infrastructure

Data integration

Data security and privacy technologies

Investment strategy on technology for data stewardship

Fostering the data culture

Cultivating a data-driven culture

Overcoming resistance

Measuring cultural change

Understanding the TOM – From strategy to operation

Designing the TOM

Implementing the TOM

Evaluating and adjusting the TOM

Summary

6

Establishing a Data Governance Organization

Establishing data governance bodies

Building your team

Team structure and hierarchy

Mode of data stewardship

Data is a team sport

Creating a data governance roadmap

Creating short-term and long-term roadmaps

Risk management and mitigation

Defining KPIs

Measuring and reporting on KPIs

Using KPIs for continuous improvement

Reviewing the fitness of your data stewardship mode

Summary

7

Data Steward Roles and Responsibilities

Understanding high-level roles and responsibilities

Day-to-day activities for data stewards

RACI matrix for data governance

Establishing data quality and lineage principles and practices

Data quality

The DQM cycle

Data lineage

Setting up data classification, access control, and security

Data classification

Data access control

Data security and protection

Monitoring and ensuring data privacy and compliance

Summary

8

Effective Data Stewardship

Establishing data stewardship principles and standardizing data incident management

The data life cycle

Principles and policies

Data incident management

Defining and implementing data ownership

Defining and designing a data domain

Assigning an owner to a data domain

Day 2 for data ownership and domain

Defining a target state – What does good data stewardship look like?

Understanding the level of data complexity

Defining a target state

What does good look like for data owners?

Summary

9

Supercharge Data Governance and Stewardship with GPT

Pairing data and AI

Leveraging AI and GPT for data governance

Enhancing data quality and trust

Automation and enrichment

Driving innovation and insight

Understanding the challenges and limitations

Embracing a responsible AI framework

Best practices for responsible AI in data governance

Operationalizing a responsible AI Framework

Future of AI for data governance

Summary

Part 3: What Makes Data Stewardship a Sustainable Success?

10

Data Stewardship Best Practices

Rolling out a people-first operational model

Aligning data mindset and continuous learning

Creating a culture of accountability and ownership

Executing day-to-day data processes

Who does what, by when, and approved by whom?

Data mapping and metadata management

Data risk assessment and mitigation

Optimizing your data journey with strategic technological integration

Data stewardship tools and technologies

Data catalog and metadata

Blockchain and AI

Valuing and protecting data as an asset

Realizing short- and long-term business value via data

Summary

11

Theory versus Real Life

Understanding why there is a gap between theory and reality

Discovering the gaps

Identifying the gaps

Bridging the gap between theory and reality

Critical thinking in bridging theory and reality

Integrating data stewardship into daily operations

Gap #1 – Standard operating procedure is written but not followed

Gap #2 – Insufficient commitment from stakeholders

Gap #3 – Data governance operating model cannot keep up with ever-changing regulatory requirements

Gap #4 – Technical debt

Future-proofing your data stewardship program

Benchmarking with DAMA and EDMC surveys

Enhancing data stewards’ skills with skillset matrix

Cultivating resilience and adaptability in data stewardship

Evolving theoretical models with real-life experiences

Summary

12

Case Studies

Nurturing a data culture with a data mindset – case study #1

A plan of action

Data stewardship in action

Outcome

Streamlining fund performance and reporting – case study #2

A plan of action

Data stewardship in action

Outcome

Summary

Index

Other Books You May Enjoy

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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Part 1:Why Data Stewardship and Why Me?

Here, you will begin the foundational journey of aligning your business strategy with data strategy and stewardship in the initial chapters of this insight-packed book. You will discover how to unlock the latent value of data, develop the required mindset and skillset, and transition seamlessly from strategic planning to execution. These chapters are crafted to guide you through the inception of data stewardship, demonstrating its organizational benefits and providing a practical roadmap to initiate a robust data stewardship program.

This part has the following chapters:

Chapter 1, From Business Strategy to Data Strategy to Data Stewardship

Chapter 2, How Data Stewardship Can Help Your Organization

Chapter 3, Getting Started with the Data Stewardship Program

1

From Business Strategy to Data Strategy to Data Stewardship

Data is the new oil

Data is the new currency

Data is the common language

All these buzz-phrases fail to resonate when you are trying to secure a budget for data programs in a management meeting. Distracted stakeholders, lack of impact, and stagnating initiatives often become the norm as data quality issues mount and data compliance challenges multiply.

Everyone recognizes the need for a data-driven culture, yet nobody wants to own the responsibility. Conducting a lot of data workshops will not bring you closer to your objectives if data stewardship and strategy are not aligned with the business strategy.

The struggle is real and the cycle is repetitive – once you leave the organization after years of struggle, your successor restarts the data stewardship program, and the story replays.

Does this sound familiar to you?

As a data professional, it is unrealistic for you to expect other business functions to dedicate time to understanding data intricacies, just as you would not spend days learning about marketing, HR, or accounting.

The key question for your audience is the following: What is in it for me?

Consider redefining your data initiatives, including a data stewardship program, as a solution to practical problems: freeing up Friday nights spent on report consolidation, introducing efficient self-service data analytics tools, and offering potential bonuses tied to meeting data quality metrics.

Now we are talking.

Data stewardship is not limited to a data workshop or two. It’s a direction, a mindset, and a problem-solving mechanism. In the first chapter, we’ll emphasize the pivotal role of data stewardship in aligning data initiatives with business strategy and solving real business issues.

Then how does data stewardship relate to the business strategy?

Again, think from the C-level perspective – what is in it for the senior executives if they invest x amount of money and y amount of head counts into data stewardship initiatives?

So, what is data stewardship and why is it essential? We will explore these questions and a few more in this chapter.

In this chapter, we will discuss the following:

Understanding the strategic, tactical, and operational value of data stewardship

Unlocking business value with data stewardship

Exploring the mindset and skillset gap

Translating strategy into execution

Decoding data governance, management, and stewardship

Understanding the strategic, tactical, and operational value of data stewardship

Data stewardship is the practice of managing data ethically and responsibly. Data stewards are responsible for ensuring that data is used in a way that respects the rights of individuals and meets the business objectives of the organization. Data stewardship requires a holistic approach to data management. It involves developing a data strategy that aligns with the organization’s business strategy, establishing data governance policies and procedures, and designing data models and architectures that can support the implementation of an automated data operating model on the cloud. All of these only make sense if you can tie them to business objectives.

Now, we will look at how data stewardship is related to business strategy and how it can help businesses achieve their goals. We will also discuss how to develop a data strategy that aligns with the business strategy and how to identify the key stakeholders involved in the data stewardship process. Finally, we will discuss how to develop a data stewardship program that will help businesses unlock the value of their data.

Bridging the gap between data strategy and data operation

Data stewardship is not a tick-box exercise. It is a continuous refinement of your data operation to support your new business model. You need to tackle from strategic, tactical, and operational levels (Figure 1.1) to make it a sustainable program and ensure that it meets both short- and long-term business objectives horizontally and vertically:

Strategic: It’s designed with the entire organization in mind and begins with an organization’s mission. This will also influence the culture within an organization.

Tactical: It describes the series of plans to achieve the ambitions outlined in the strategy.

Operational: It is highly specific with a measurable metric and usually couples with standard operating procedures (SOPs) to ensure the consistency of operation excellence.

Figure 1.1 shows how a high-level strategy gets broken down into mid-level tactical plans, and then finally into on-the-ground operations.

Figure 1.1 – An organizational view of data stewardship

It is a business-friendly way to visualize how things get done in a big