Data Stewardship: An Actionable Guide to Effective Data Management and Data Governance

Elsevier Science, 15.11.2020 - 326 Seiten
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Data Stewardship, Second Edition, provides clear, concise and 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 a 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.

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 several 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 most importantly, a pivot in the overall thinking around the best way to perform data stewardship - moving from business/organizational function to data domain.

  • Features 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 domains, domain structures, and governance by data domains
  • Integrates data governance into project methodology, defining roles on a project, adding DG tasks to the WBS, and discussing how to include DG in the PMO
  • Investigates additional important roles for Data Stewards related to Data Lineage, Process Risk Management, and Data Lifecycle Management

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Über den Autor (2020)

David Plotkin is an Advisory Consultant for EMC2, working in Enterprise Information Management. He is responsible for leading efforts at client companies to plan and implement Data Governance both as stand-alone efforts and as part of other initiatives such as Data Quality improvement and Master Data Management. He has previously managed Data Governance at an insurance company and managed data quality at two large banks. He has been working with data governance, data modeling, metadata and data quality for over 20 years. He is a popular speaker at DAMA chapters and conferences, and serves as a subject matter expert on many topics around metadata, data governance, and data quality.

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