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1. Highly Relevant and Approachable
   Having worked in the data space as a project manager, program manager, and scrum master, I can tell you the one term that both strikes terror and makes eyes glaze over is “data governance.”Wendy deftly demonstrates a command over data governance with a level of credibility which shows she’s been there several times. She shares her experiences and advice in a way that works across organizational cultures, complexity and size of data solutions, and skill/roles of your data team.In short she demystifies data governance in a way which makes the topic approachable from just about any conceivable angle. Whether you’re new to the topic or you’re jaded by the “been there, done that” of having been burned, she has your back.

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2. A Must-Read for Navigating Data Governance with Ease and Practicality
   This is a standout resource for anyone involved in data, technology, or business strategy. What really sets this book apart is how it breaks down complex governance concepts into clear, actionable steps. Wendy provides practical frameworks that show how data governance directly ties to business outcomes, making the material relevant for both experienced data professionals as well as those newer to the field.If you’re looking to build trust in data and gain a solid understanding of effective governance practices, this book is an invaluable guide.

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3. Enterprise Data Governance Practice
   Just finished another “data centric” book. A big part of managing data across an enterprise includes establishing an effective data governance practice. I was excited about being asked to review this book.The author identifies the book’s audience as Chief data officer (CDO), data governance leaders, data stewards, and engineers. I found it to be a good reference for anyone who works with data (especially data engineers, data scientists, database professionals and data analysts) – I’m still wondering when we will see an increase in “Data Protection” books by Cybersecurity professionals.The book opens with a practical definition for data governance – Once the reader begins to understand the significance of data governance, the book transitions to getting “buy in” for data governance policies.Data governance models are discussed (example: federated, semi-federated, and hub spoke model) – as well as data governance roles and responsibilities.How do you define a successful Data Governance program? What is Metadata, Data lineage and Data quality? What is the Relationship between data management (Data Operations) and data architecture?How do you implement automation in a data governance practice and how do you communicate data governance insights and concerns to multiple audiences (tech and business)?

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4. Not just for Data Governance; but for pitching any high level plan
   Before I start, the techniques in this book can be used to pitch almost anything to management. Having a clear, concise, and simple vision, having a readiness model, how to refine the readiness model: This can be applied to AI, Software, Hardware, etc. I think the author went above and beyond in not only going from start to finish on how to craft a data governance strategy; but also how to deal with the various challenges that come from starting one at a large organization. I used a few techniques in the book when crafting my own data governance strategy and they have worked well so far. I’d highly recommend the book to anyone that wants a high level overview of how to pitch and manage a data governance effort. Note that this is not a technical book and as such doesn’t come with any code for it.

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5. Amazing Data Governance Handbook
   This book effectively covers data modern challenges, such as stakeholders buy-in, from advocates to team structure, communication, data management, and data-driven decision-making, providing practical case studies and frameworks. Batchelder’s insights offer a strategic roadmap for enhancing data governance to support organizational growth and innovation. This guide is a must-read for anyone looking to strengthen their data governance practices.

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