The Practitioner's Guide to Data Quality Improvement offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. It shares the fundamentals for understanding the impacts of poor data quality, and guides practitioners and managers alike in socializing, gaining sponsorship for, planning, and establishing a data quality program. It demonstrates how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. It includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning. This book is recommended for data management practitioners, including database analysts, information analysts, data administrators, data architects, enterprise architects, data warehouse engineers, and systems analysts, and their managers. Offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. Shows how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. Includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning.
Jones, D. (2012-08-15). Data quality metrics: Are you adopting the Dilbert approach?: Data quality pro journal Retrieved from Accessed 2012-08-25. Kent, W. (2000).
In this practical guide, data experts Uma Gupta and San Cannon look to demystify data governance through pragmatic advice based on real-world experience and cutting-edge academic research.
Her trademarked approach—in which she has trained Fortune 500 clients and hundreds of workshop attendees—applies to all types of data and to all types of organizations. * Includes numerous templates, detailed examples, and practical ...
It provides solutions for meeting the strategic challenges of applying analytics, such as: Integrating analytics into decision making, corporate culture, and business strategy Leading and organizing analytics within the corporation Applying ...
This volume presents a methodology for defining, measuring and improving data quality.
Data Quality: The Accuracy Dimension is about assessing the quality of corporate data and improving its accuracy using the data profiling method.
The best books occupy precious desk space, dog-eared and highlighted. By this standard, Danette McGilvray's book, Executing Data Quality Projects: Ten Steps to Quality Data and Trusted InformationTM, will be absolutely ravaged, ...
Mikel J. Harry, Prem S. Mann, Ofelia C. De Hodgins, Richard L. Hulbert, Christopher J. Lacke. a particular product characteristic. ... G. E.P. Box, W. G. Hunter, and S.Hunter, Statistics for Experimenters, Wiley, NewYork, 1978. 2.
In this comprehensive book, Rupa Mahanti provides guidance on the different aspects of data quality with the aim to be able to improve data quality.
The book begins with an overview list of 8-10 precepts associated with a business-focused view of the knowledge necessary for developing customer-oriented business processes that lead to excellent customer experiences resulting in increased ...