Data Stewardship in Action: A roadmap to Data Value Realization and Measurable Business Outcomes PuiShing LEE

Data Stewardship in Action
Foreword
Contributors
About the author
About the reviewers
Preface
   Who this book is for
   What this book covers
   To get the most out of this book
   Conventions used
   Get in touch
   Share Your Thoughts
   Download a free PDF copy of this book
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
   Why subscribe?
Other Books You May Enjoy
   Packt is searching for authors like you
   Share Your Thoughts
   Download a free PDF copy of this book