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Data Stewardship,

Edition 2 An Actionable Guide to Effective Data Management and Data Governance

Editors: By David Plotkin

Publication Date: 06 Nov 2020

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Data stewards in any organization are the backbone of a successful data governance implementation because they do the work to make data trusted, dependable, and high quality. Since the publication of the first edition, there have been critical new developments in the field, such as integrating Data Stewardship into project management, handling Data Stewardship in large international companies, handling "big data" and Data Lakes, and a pivot in the overall thinking around the best way to align data stewardship to the data—moving from business/organizational function to data domain. Furthermore, the role of process in data stewardship is now recognized as key and needed to be covered.Data Stewardship, Second Edition provides clear and concise practical advice on implementing and running data stewardship, including guidelines on how to organize based on organizational/company structure, business functions, and data ownership. The book shows data managers how to gain support for a stewardship effort, maintain that support over the long-term, and measure the success of the data stewardship effort. It includes detailed lists of responsibilities for each type of data steward and strategies to help the Data Governance Program Office work effectively with the data stewards.

Key Features

Includes an enhanced section on data governance/stewardship structure for companies that do business internationally, including the structure of business terms to account for country differences
Outlines the advantages and disadvantages of "data domains," details on suggested data domains and data domain structures, as well as data governance by data domains
Integrates data governance into Project methodology, defining roles on a project, adding Data Governance tasks to the Work Breakdown Structure, as well as advantages of working closely with the Project management Office
Covers the data stewardship involved in implementing national and international data privacy regulations

About the author

By David Plotkin, Advisory Consultant, EMC2, working in Enterprise Information Management

1. Data Stewardship and Data Governance: How They Fit Together2. Understanding the Types of Data Stewardship3. Data Stewardship Roles and Responsibilities4. Implementing Data Stewardship5. Training Business Data Stewards6. Practical Data Stewardship7. Important Roles of Data Stewards8. Measuring Data Stewardship Progress: The Metrics9. Rating Your Data Stewardship Maturity10. Big Data Stewardship and Data Lakes11. Governing and Stewarding your Data using Data Domains12. Summing It All UpAppendixA: Example Definition and DerivationB: Sample Training Plan Outlines

Title Reviews

"If you work in the field of data management, chance are you know of David Plotkin. He has worked in the field for decades and has written extensively on data, metadata, and related issues. With the second edition of his book, Plotkin has written the quintessential book on data stewardship. He defines data stewardship and how it fits together with data governance, delivering best practices, policies, and procedures that make sense. The book offers up practical advice on implementing data stewardship and defines the roles and responsibilities of the data steward. But he also devotes a chapter offering guidance on training for data stewards, and another chapter on the metrics that can be used to measure the performance of data stewards. And if your organization is new or just starting to implementing data governance and stewardship, then you absolutely must read Chapter 4, “Implementing Data Stewardship.¿ It will step you through the process of championing, communicating, and gaining support for data stewardship."—Data and Technology Today

ISBN: 9780128221327

Page Count: 322

Retail Price (USD) :

9781935504856; 9780071744584

Data science and data engineering professionals as well as researchers and engineers who need to ensure consistent, accurate and reliable data across their company, lab, hospital, etc.