Data Quality Procedures
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Data Quality
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Author : Thomas C. Redman
language : en
Publisher: Random House Puzzles & Games
Release Date : 1992
Data Quality written by Thomas C. Redman and has been published by Random House Puzzles & Games this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Computers categories.
Data Quality begins with an explanation of what data is, how it is created and destroyed, then explores the true quality of data--accuracy, consistency and currentness. From there, the author covers the powerful methods of statistical quality control and process management to bear on the core processes that create, manipulate, use and store data values. Table of Contents: 1. Introduction; 2. Data and Information; 3. Dimensions of Data Quality; 4. Statistical Quality Control; 5. Process Management; 6. Process Representation and the Functions of Information Processing Approach; 7. Data Quality Requirements; 8. Measurement Systems and Data Quality; 9. Process Redesign Using Experimentation and Computer Simulation; 10. Managing Multiple Processes; 11. Perspective Prospects and Implications; 12. Summaries.
Handbook Of Data Quality
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Author : Shazia Sadiq
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-08-13
Handbook Of Data Quality written by Shazia Sadiq and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-13 with Computers categories.
The issue of data quality is as old as data itself. However, the proliferation of diverse, large-scale and often publically available data on the Web has increased the risk of poor data quality and misleading data interpretations. On the other hand, data is now exposed at a much more strategic level e.g. through business intelligence systems, increasing manifold the stakes involved for individuals, corporations as well as government agencies. There, the lack of knowledge about data accuracy, currency or completeness can have erroneous and even catastrophic results. With these changes, traditional approaches to data management in general, and data quality control specifically, are challenged. There is an evident need to incorporate data quality considerations into the whole data cycle, encompassing managerial/governance as well as technical aspects. Data quality experts from research and industry agree that a unified framework for data quality management should bring together organizational, architectural and computational approaches. Accordingly, Sadiq structured this handbook in four parts: Part I is on organizational solutions, i.e. the development of data quality objectives for the organization, and the development of strategies to establish roles, processes, policies, and standards required to manage and ensure data quality. Part II, on architectural solutions, covers the technology landscape required to deploy developed data quality management processes, standards and policies. Part III, on computational solutions, presents effective and efficient tools and techniques related to record linkage, lineage and provenance, data uncertainty, and advanced integrity constraints. Finally, Part IV is devoted to case studies of successful data quality initiatives that highlight the various aspects of data quality in action. The individual chapters present both an overview of the respective topic in terms of historical research and/or practice and state of the art, as well as specific techniques, methodologies and frameworks developed by the individual contributors. Researchers and students of computer science, information systems, or business management as well as data professionals and practitioners will benefit most from this handbook by not only focusing on the various sections relevant to their research area or particular practical work, but by also studying chapters that they may initially consider not to be directly relevant to them, as there they will learn about new perspectives and approaches.
Executing Data Quality Projects
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Author : Danette McGilvray
language : en
Publisher: Elsevier
Release Date : 2008-09-01
Executing Data Quality Projects written by Danette McGilvray and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-01 with Computers categories.
Information is currency. Recent studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. In this important and timely new book, Danette McGilvray presents her “Ten Steps approach to information quality, a proven method for both understanding and creating information quality in the enterprise. 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 advice for executing every step of the “Ten Steps approach.* Allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices.* A companion Web site includes links to numerous data quality resources, including many of the planning and information-gathering templates featured in the text, quick summaries of key ideas from the Ten Step methodology, and other tools and information available online.
The Practitioner S Guide To Data Quality Improvement
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Author : David Loshin
language : en
Publisher: Elsevier
Release Date : 2010-11-22
The Practitioner S Guide To Data Quality Improvement written by David Loshin and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-22 with Computers categories.
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.
Data Quality For The Information Age
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Author : Thomas C. Redman
language : en
Publisher: Artech House Publishers
Release Date : 1996
Data Quality For The Information Age written by Thomas C. Redman and has been published by Artech House Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Computers categories.
All aspects of data management are explored in this title, which provides detailed analyses of quality problems and their impacts, potential solutions and how they are combined to form an overall data quality program, senior management's role, and methods used to make and sustain improvements.
Guidance For The Data Quality Objectives Process
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Author : United States. Environmental protection agency. Office of environmental information (Washington DC).
language : en
Publisher: DIANE Publishing
Release Date : 2000
Guidance For The Data Quality Objectives Process written by United States. Environmental protection agency. Office of environmental information (Washington DC). and has been published by DIANE Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with categories.
Data Quality
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Author : British Standards Institution
language : en
Publisher:
Release Date : 2020
Data Quality written by British Standards Institution and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Data Quality
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Author : British Standards Institution
language : en
Publisher:
Release Date : 2023
Data Quality written by British Standards Institution and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
A Process View Of Data Quality Classic Reprint
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Author : Henry Kon
language : en
Publisher: Forgotten Books
Release Date : 2018-02-11
A Process View Of Data Quality Classic Reprint written by Henry Kon and has been published by Forgotten Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-11 with Business & Economics categories.
Excerpt from A Process View of Data Quality We posit that the term data quality, though used in a variety of research and practitioner contexts, has been inadequately conceptualized and defined. To improve data quality, we must bound and define the concept of data quality. In the past, researchers have tended to take a product oriented view of data quality. Though necessary, this view is insufficient for three reasons. First, data quality defects in general, are difficult to detect by simple inspection of the data product. Second, definitions of data quality dimensions and defects, while useful intuitively, tend to be ambiguous and interdependent. Third, in line with a cornerstone of tqm philosophy, emphasis should be placed on process management to improve product quality. The objective of this paper is to characterize the concept of data quality from a mess perspective. A formal process model of an information system (is) is developed which offers precise process constructs for characterizing data quality. With these constructs, we rigorously define the key dimensions of data quality. The analysis also provides a framework for examining the cm data quality problems. Finally, facilitated by the exactness of the model, an analysis is presented of the interdependencies among the various data quality dimensions. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
Data Quality For Decision Makers
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Author : Guilherme Morbey
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-05
Data Quality For Decision Makers written by Guilherme Morbey and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-05 with Business & Economics categories.
Currently many companies are confronted with the decision how to deal with the new data quality requirements of the regulatory authorities. Future data quality statements for enterprise key figures and their origins are being demanded. Applying methods of a data quality management system can produce these statements best. Guilherme Morbey explains the introduction of such a system in the form of a dialogue.