Data Stewardship in Action : A Roadmap to Data Value Realization and Measurable Business Outcomes / Pui Shing Lee and Toa Charm.

Format:

Book

Author/Creator:

Lee, Pui Shing, author.

Zhan, Jiayang, author.

Language:

English

Subjects (All):

Information technology--Security measures.

Information technology.

Data protection.

Data warehousing.

Physical Description:

1 online resource (272 pages)

Edition:

First edition.

Place of Publication:

Birmingham, England : Packt Publishing Ltd., [2024]

Biography/History:

Lee Pui Shing: 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 like 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.

Summary:

Take your organization's data maturity to the next level by operationalizing data governance Key Features Develop the mindset and skills essential for successful data stewardship Apply practical advice and industry best practices, spanning data governance, quality management, and compliance, to enhance data stewardship Follow a step-by-step program to develop a data operating model and implement data stewardship effectively Purchase of the print or Kindle book includes a free PDF eBook Book Description 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. What you will learn Enhance your job prospects by understanding the data stewardship field, roles, and responsibilities Discover how to develop a data strategy and translate it into a functional data operating model Develop an effective and efficient data stewardship program Gain practical experience of establishing a data stewardship initiative Implement purposeful governance with measurable ROI Prioritize data use cases with the value and effort matrix Who this book is for This book is for professionals working in the field of data management, including business analysts, data scientists, and data engineers looking to gain a deeper understanding of the data steward role. Senior executives who want to (re)establish the data governance body in their organizations will find this resource invaluable. While accessible to both beginners and professionals, basic knowledge of data management concepts, such as data modeling, data warehousing, and data quality, is a must to get started.

Contents:

Cover

Title Page

Copyright and Credits

Dedication

Foreword

Contributors

Table of Contents

Preface

Part 1: Why Data Stewardship and Why Me?

Chapter 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 don different hats

Summary

Chapter 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

Chapter 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

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

Chapter 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

Chapter 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 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

Chapter 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

Chapter 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

Chapter 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?

Chapter 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

Part 3: What Makes Data Stewardship a Sustainable Success?

Chapter 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

Chapter 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

Chapter 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

Index

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Notes:

Description based upon print version of record.

Fostering the data culture

Description based on print version record.

ISBN:

9781837638123

1837638128

OCLC:

1420630891