Data Quality

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Data Quality

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Author : Thomas C. Redman
language : en
Publisher: Digital Press
Release Date : 2001-01-11

Data Quality written by Thomas C. Redman and has been published by Digital Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-01-11 with Computers categories.

Can any subject inspire less excitement than "data quality"? Yet a moment's thought reveals the ever-growing importance of quality data. From restated corporate earnings, to incorrect prices on the web, to the bombing of the Chinese Embassy, the media reports the impact of poor data quality on a daily basis. Every business operation creates or consumes huge quantities of data. If the data are wrong, time, money, and reputation are lost. In today's environment, every leader, every decision maker, every operational manager, every consumer, indeed everyone has a vested interest in data quality. Data Quality: The Field Guide provides the practical guidance needed to start and advance a data quality program. It motivates interest in data quality, describes the most important data quality problems facing the typical organization, and outlines what an organization must do to improve. It consists of 36 short chapters in an easy-to-use field guide format. Each chapter describes a single issue and how to address it. The book begins with sections that describe why leaders, whether CIOs, CFOs, or CEOs, should be concerned with data quality. It explains the pros and cons of approaches for addressing the issue. It explains what those organizations with the best data do. And it lays bare the social issues that prevent organizations from making headway. "Field tips" at the end of each chapter summarize the most important points. Allows readers to go directly to the topic of interest Provides web-based material so readers can cut and paste figures and tables into documents within their organizations Gives step-by-step instructions for applying most techniques and summarizes what "works"

Data Quality

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Author : Prashanth Southekal
language : en
Publisher: John Wiley & Sons
Release Date : 2023-02-01

Data Quality written by Prashanth Southekal and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-01 with Business & Economics categories.

Discover how to achieve business goals by relying on high-quality, robust data In Data Quality: Empowering Businesses with Analytics and AI, veteran data and analytics professional delivers a practical and hands-on discussion on how to accelerate business results using high-quality data. In the book, you’ll learn techniques to define and assess data quality, discover how to ensure that your firm’s data collection practices avoid common pitfalls and deficiencies, improve the level of data quality in the business, and guarantee that the resulting data is useful for powering high-level analytics and AI applications. The author shows you how to: Profile for data quality, including the appropriate techniques, criteria, and KPIs Identify the root causes of data quality issues in the business apart from discussing the 16 common root causes that degrade data quality in the organization. Formulate the reference architecture for data quality, including practical design patterns for remediating data quality Implement the 10 best data quality practices and the required capabilities for improving operations, compliance, and decision-making capabilities in the business An essential resource for data scientists, data analysts, business intelligence professionals, chief technology and data officers, and anyone else with a stake in collecting and using high-quality data, Data Quality: Empowering Businesses with Analytics and AI will also earn a place on the bookshelves of business leaders interested in learning more about what sets robust data apart from the rest.

Data Quality

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Author : Yng-Yuh Richard Wang
language : en
Publisher: Springer Science & Business Media
Release Date : 2001

Data Quality written by Yng-Yuh Richard Wang 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 2001 with Business & Economics categories.

Data Quality provides an exposé of research and practice in the data quality field for technically oriented readers. It is based on the research conducted at the MIT Total Data Quality Management (TDQM) program and work from other leading research institutions. This book is intended primarily for researchers, practitioners, educators and graduate students in the fields of Computer Science, Information Technology, and other interdisciplinary areas. It forms a theoretical foundation that is both rigorous and relevant for dealing with advanced issues related to data quality. Written with the goal to provide an overview of the cumulated research results from the MIT TDQM research perspective as it relates to database research, this book is an excellent introduction to Ph.D. who wish to further pursue their research in the data quality area. It is also an excellent theoretical introduction to IT professionals who wish to gain insight into theoretical results in the technically-oriented data quality area, and apply some of the key concepts to their practice.

Data Quality

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Author : Jack E. Olson
language : en
Publisher: Elsevier
Release Date : 2003-01-09

Data Quality written by Jack E. Olson and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-01-09 with Computers categories.

Data Quality: The Accuracy Dimension is about assessing the quality of corporate data and improving its accuracy using the data profiling method. Corporate data is increasingly important as companies continue to find new ways to use it. Likewise, improving the accuracy of data in information systems is fast becoming a major goal as companies realize how much it affects their bottom line. Data profiling is a new technology that supports and enhances the accuracy of databases throughout major IT shops. Jack Olson explains data profiling and shows how it fits into the larger picture of data quality.* Provides an accessible, enjoyable introduction to the subject of data accuracy, peppered with real-world anecdotes. * Provides a framework for data profiling with a discussion of analytical tools appropriate for assessing data accuracy. * Is written by one of the original developers of data profiling technology. * Is a must-read for any data management staff, IT management staff, and CIOs of companies with data assets.

Data Quality Fundamentals

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Author : Barr Moses
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-09-01

Data Quality Fundamentals written by Barr Moses and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-01 with Computers categories.

Do your product dashboards look funky? Are your quarterly reports stale? Is the data set you're using broken or just plain wrong? These problems affect almost every team, yet they're usually addressed on an ad hoc basis and in a reactive manner. If you answered yes to these questions, this book is for you. Many data engineering teams today face the "good pipelines, bad data" problem. It doesn't matter how advanced your data infrastructure is if the data you're piping is bad. In this book, Barr Moses, Lior Gavish, and Molly Vorwerck, from the data observability company Monte Carlo, explain how to tackle data quality and trust at scale by leveraging best practices and technologies used by some of the world's most innovative companies. Build more trustworthy and reliable data pipelines Write scripts to make data checks and identify broken pipelines with data observability Learn how to set and maintain data SLAs, SLIs, and SLOs Develop and lead data quality initiatives at your company Learn how to treat data services and systems with the diligence of production software Automate data lineage graphs across your data ecosystem Build anomaly detectors for your critical data assets

Data Quality

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Author : Rupa Mahanti
language : en
Publisher: Quality Press
Release Date : 2019-03-18

Data Quality written by Rupa Mahanti and has been published by Quality Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-18 with Computers categories.

Good data is a source of myriad opportunities, while bad data is a tremendous burden. Companies that manage their data effectively are able to achieve a competitive advantage in the marketplace, while bad data, like cancer, can weaken and kill an organization. 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. Specifically, the book addresses: Causes of bad data quality, bad data quality impacts, and importance of data quality to justify the case for data quality Butterfly effect of data quality A detailed description of data quality dimensions and their measurement Data quality strategy approach Six Sigma - DMAIC approach to data quality Data quality management techniques Data quality in relation to data initiatives like data migration, MDM, data governance, etc. Data quality myths, challenges, and critical success factors Students, academicians, professionals, and researchers can all use the content in this book to further their knowledge and get guidance on their own specific projects. It balances technical details (for example, SQL statements, relational database components, data quality dimensions measurements) and higher-level qualitative discussions (cost of data quality, data quality strategy, data quality maturity, the case made for data quality, and so on) with case studies, illustrations, and real-world examples throughout. About the Author Rupa Mahanti, Ph.D. is a Business and Information Management consultant and has worked in different solution environments and industry sectors in the United States, United Kingdom, India, and Australia. She helps clients with activities such as business process mapping, information management, data quality, and strategy. Having a work experience (academic, industry, and research) of more than a decade and half, Rupa has guided a doctoral dissertation and published a large number of research articles. She is an associate editor with the journal Software Quality Professional and a reviewer for several international journals. "This is not the kind of book that you'll read one time and be done with. So scan it quickly the first time through to get an idea of its breadth. Then dig in on one topic of special importance to your work. Finally, use it as a reference to guide your next steps, learn details, and broaden your perspective." from the foreword by Thomas C. Redman, Ph.D., the Data Doc Dr. Mahanti provides a very detailed and thorough coverage of all aspects of data quality management that would suit all ranges of expertise from a beginner to an advanced practitioner. With plenty of examples, diagrams, etc. the book is easy to follow and will deepen your knowledge in the data domain. I will certainly keep this handy as my go-to reference. I can't imagine the level of effort and passion that Dr. Mahanti has put into this book that captures so much knowledge and experience for the benefit of the reader. I would highly recommend this book for its comprehensiveness, depth, and detail. A must-have for a data practitioner at any level. Clint D'Souza, CEO and Director, CDZM Consulting

Executing Data Quality Projects

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Author : Danette McGilvray
language : en
Publisher: Academic Press
Release Date : 2021-05-27

Executing Data Quality Projects written by Danette McGilvray and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-27 with Computers categories.

Executing Data Quality Projects, Second Edition presents a structured yet flexible approach for creating, improving, sustaining and managing the quality of data and information within any organization. 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. Help is here! This book describes a proven Ten Step approach that combines a conceptual framework for understanding information quality with techniques, tools, and instructions for practically putting the approach to work – with the end result of high-quality trusted data and information, so critical to today's data-dependent organizations. The Ten Steps approach applies to all types of data and all types of organizations – for-profit in any industry, non-profit, government, education, healthcare, science, research, and medicine. This book includes numerous templates, detailed examples, and practical advice for executing every step. At the same time, readers are advised on how to select relevant steps and apply them in different ways to best address the many situations they will face. The layout allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, best practices, and warnings. The experience of actual clients and users of the Ten Steps provide real examples of outputs for the steps plus highlighted, sidebar case studies called Ten Steps in Action. This book uses projects as the vehicle for data quality work and the word broadly to include: 1) focused data quality improvement projects, such as improving data used in supply chain management, 2) data quality activities in other projects such as building new applications and migrating data from legacy systems, integrating data because of mergers and acquisitions, or untangling data due to organizational breakups, and 3) ad hoc use of data quality steps, techniques, or activities in the course of daily work. The Ten Steps approach can also be used to enrich an organization's standard SDLC (whether sequential or Agile) and it complements general improvement methodologies such as six sigma or lean. No two data quality projects are the same but the flexible nature of the Ten Steps means the methodology can be applied to all. The new Second Edition highlights topics such as artificial intelligence and machine learning, Internet of Things, security and privacy, analytics, legal and regulatory requirements, data science, big data, data lakes, and cloud computing, among others, to show their dependence on data and information and why data quality is more relevant and critical now than ever before. - Includes concrete instructions, numerous templates, and practical advice for executing every step of The Ten Steps approach - Contains real examples from around the world, gleaned from the author's consulting practice and from those who implemented based on her training courses and the earlier edition of the book - 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 templates featured in the text, quick summaries of key ideas from the Ten Steps methodology, and other tools and information that are available online

Data Quality

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Author : Carlo Batini
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-09-27

Data Quality written by Carlo Batini 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 2006-09-27 with Computers categories.

Poor data quality can seriously hinder or damage the efficiency and effectiveness of organizations and businesses. The growing awareness of such repercussions has led to major public initiatives like the "Data Quality Act" in the USA and the "European 2003/98" directive of the European Parliament. Batini and Scannapieco present a comprehensive and systematic introduction to the wide set of issues related to data quality. They start with a detailed description of different data quality dimensions, like accuracy, completeness, and consistency, and their importance in different types of data, like federated data, web data, or time-dependent data, and in different data categories classified according to frequency of change, like stable, long-term, and frequently changing data. The book's extensive description of techniques and methodologies from core data quality research as well as from related fields like data mining, probability theory, statistical data analysis, and machine learning gives an excellent overview of the current state of the art. The presentation is completed by a short description and critical comparison of tools and practical methodologies, which will help readers to resolve their own quality problems. This book is an ideal combination of the soundness of theoretical foundations and the applicability of practical approaches. It is ideally suited for everyone – researchers, students, or professionals – interested in a comprehensive overview of data quality issues. In addition, it will serve as the basis for an introductory course or for self-study on this topic.

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.

Managing Data Quality

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Author : Tim King
language : en
Publisher: BCS, The Chartered Institute for IT
Release Date : 2020-04-27

Managing Data Quality written by Tim King and has been published by BCS, The Chartered Institute for IT this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-27 with categories.

This book explains data quality management in practical terms, focusing on three key areas - the nature of data in enterprises, the purpose and scope of data quality management, and implementing a data quality management system, in line with ISO 8000-61. Examples of good practice in data quality management are also included.