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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.
- 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
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.
1 Data Stewardship and Data Governance: How They Fit Together
2 Understanding the Types of Data Stewardship
3 Data Stewardship Roles and Responsibilities
4 Implementing Data Stewardship
5 Training Business Data Stewards
6 Practical Data Stewardship
7 Important Roles of Data Stewards
8 Measuring Data Stewardship Progress: The Metrics
9 Rating Your Data Stewardship Maturity
10 Big Data Stewardship and Data Lakes
11 Governing and Stewarding your Data using Data Domains
12 Summing It All Up
A: Example Definition and Derivation
B: Sample Training Plan Outlines
- No. of pages:
- © Academic Press 2021
- 15th November 2020
- Academic Press
- Paperback ISBN:
David Plotkin has 30 years of experience in data governance, data modeling, metadata, and data quality. He has led efforts at employers and 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 two insurance companies and managed data quality at two large banks. He is a popular speaker at DAMA courses and conferences and serves as a subject matter expert on many topics around metadata, data governance, and data quality.
Advisory Consultant, EMC2, working in Enterprise Information Management
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