The Practitioner S Guide To Data Quality Improvement
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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.
The Practitioner S Guide To Data Quality Improvement
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Author : D. Loshin
language : en
Publisher:
Release Date : 2013
The Practitioner S Guide To Data Quality Improvement written by D. Loshin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
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.
Measuring Data Quality For Ongoing Improvement
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Author : Laura Sebastian-Coleman
language : en
Publisher: Newnes
Release Date : 2012-12-31
Measuring Data Quality For Ongoing Improvement written by Laura Sebastian-Coleman and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-31 with Computers categories.
The Data Quality Assessment Framework shows you how to measure and monitor data quality, ensuring quality over time. You'll start with general concepts of measurement and work your way through a detailed framework of more than three dozen measurement types related to five objective dimensions of quality: completeness, timeliness, consistency, validity, and integrity. Ongoing measurement, rather than one time activities will help your organization reach a new level of data quality. This plain-language approach to measuring data can be understood by both business and IT and provides practical guidance on how to apply the DQAF within any organization enabling you to prioritize measurements and effectively report on results. Strategies for using data measurement to govern and improve the quality of data and guidelines for applying the framework within a data asset are included. You'll come away able to prioritize which measurement types to implement, knowing where to place them in a data flow and how frequently to measure. Common conceptual models for defining and storing of data quality results for purposes of trend analysis are also included as well as generic business requirements for ongoing measuring and monitoring including calculations and comparisons that make the measurements meaningful and help understand trends and detect anomalies. - Demonstrates how to leverage a technology independent data quality measurement framework for your specific business priorities and data quality challenges - Enables discussions between business and IT with a non-technical vocabulary for data quality measurement - Describes how to measure data quality on an ongoing basis with generic measurement types that can be applied to any situation
Journey To Data Quality
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Author : Yang W. Lee
language : en
Publisher: MIT Press (MA)
Release Date : 2006
Journey To Data Quality written by Yang W. Lee and has been published by MIT Press (MA) this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Business & Economics categories.
All organizations today confront data quality problems, both systemic and structural. Neither ad hoc approaches nor fixes at the systems level--installing the latest software or developing an expensive data warehouse--solve the basic problem of bad data quality practices. Journey to Data Qualityoffers a roadmap that can be used by practitioners, executives, and students for planning and implementing a viable data and information quality management program. This practical guide, based on rigorous research and informed by real-world examples, describes the challenges of data management and provides the principles, strategies, tools, and techniques necessary to meet them. The authors, all leaders in the data quality field for many years, discuss how to make the economic case for data quality and the importance of getting an organization's leaders on board. They outline different approaches for assessing data, both subjectively (by users) and objectively (using sampling and other techniques). They describe real problems and solutions, including efforts to find the root causes of data quality problems at a healthcare organization and data quality initiatives taken by a large teaching hospital. They address setting company policy on data quality and, finally, they consider future challenges on the journey to data quality.
Mclaughlin Kaluzny S Continuous Quality Improvement In Health Care
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Author : Julie K. Johnson
language : en
Publisher: Jones & Bartlett Learning
Release Date : 2018-10-05
Mclaughlin Kaluzny S Continuous Quality Improvement In Health Care written by Julie K. Johnson and has been published by Jones & Bartlett Learning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-05 with Health & Fitness categories.
Through a unique interdisciplinary perspective on quality management in health care, this text covers the subjects of operations management, organizational behavior, and health services research. With a particular focus on Total Quality Management (TQM) and Continuous Quality Improvement (CQI), the challenges of implementation and institutionalization are addressed using examples from a variety of health care organizations, including primary care clinics, hospital laboratories, public health departments, and academic health centers. Significantly revised throughout, the Fifth Edition offers a greater focus on application techniques, and features 14 chapters in lieu of the prior edition's 20 chapters, making it an even more effective teaching tool. New chapters have been incorporated on Implementation Science (3), Lean Six Sigma (6), and Classification and the Reduction of Medical Errors (10).
Building Capacity For Health Informatics In The Future
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Author : F. Lau
language : en
Publisher: IOS Press
Release Date : 2017-03
Building Capacity For Health Informatics In The Future written by F. Lau and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03 with Medical categories.
Health information technologies are revolutionizing and streamlining healthcare, and uptake continues to rise dramatically. If these technologies are to be effectively implemented, capacity must be built at a regional, national and global level, and the support and involvement of both government and industry will be vital. This book presents the proceedings of the 2017 Information Technology and Communications in Health conference (ITCH 2017), held in Victoria, BC, Canada, in February 2017. The conference considers, from a variety of perspectives, what is required to move the technology forward to real, sustained and widespread use, and the solutions examined range from improvements in usability and training to the need for new and improved design of information systems, user interfaces and interoperable solutions. Government policies, mandates, initiatives and the need for regulation are also explored, as is the requirement for improved interaction between industrial, governmental and academic partners. With its focus on building the next generation of health informatics and the capacity required to deliver better healthcare worldwide, this book will be of interest to all those involved in the provision of healthcare.
Practitioner S Guide To Statistics And Lean Six Sigma For Process Improvements
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Author : Mikel J. Harry
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-20
Practitioner S Guide To Statistics And Lean Six Sigma For Process Improvements written by Mikel J. Harry 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 2011-09-20 with Technology & Engineering categories.
This hands-on book presents a complete understanding of Six Sigma and Lean Six Sigma through data analysis and statistical concepts In today's business world, Six Sigma, or Lean Six Sigma, is a crucial tool utilized by companies to improve customer satisfaction, increase profitability, and enhance productivity. Practitioner's Guide to Statistics and Lean Six Sigma for Process Improvements provides a balanced approach to quantitative and qualitative statistics using Six Sigma and Lean Six Sigma methodologies. Emphasizing applications and the implementation of data analyses as they relate to this strategy for business management, this book introduces readers to the concepts and techniques for solving problems and improving managerial processes using Six Sigma and Lean Six Sigma. Written by knowledgeable professionals working in the field today, the book offers thorough coverage of the statistical topics related to effective Six Sigma and Lean Six Sigma practices, including: Discrete random variables and continuous random variables Sampling distributions Estimation and hypothesis tests Chi-square tests Analysis of variance Linear and multiple regression Measurement analysis Survey methods and sampling techniques The authors provide numerous opportunities for readers to test their understanding of the presented material, as the real data sets, which are incorporated into the treatment of each topic, can be easily worked with using Microsoft Office Excel, Minitab, MindPro, or Oracle's Crystal Ball software packages. Examples of successful, complete Six Sigma and Lean Six Sigma projects are supplied in many chapters along with extensive exercises that range in level of complexity. The book is accompanied by an extensive FTP site that features manuals for working with the discussed software packages along with additional exercises and data sets. In addition, numerous screenshots and figures guide readers through the functional and visual methods of learning Six Sigma and Lean Six Sigma. Practitioner's Guide to Statistics and Lean Six Sigma for Process Improvements is an excellent book for courses on Six Sigma and statistical quality control at the upper-undergraduate and graduate levels. It is also a valuable reference for professionals in the fields of engineering, business, physics, management, and finance.
Data And Information Quality
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Author : Carlo Batini
language : en
Publisher: Springer
Release Date : 2016-03-23
Data And Information Quality written by Carlo Batini and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-23 with Computers categories.
This book provides a systematic and comparative description of the vast number of research issues related to the quality of data and information. It does so by delivering a sound, integrated and comprehensive overview of the state of the art and future development of data and information quality in databases and information systems. To this end, it presents an extensive description of the techniques that constitute the core of data and information quality research, including record linkage (also called object identification), data integration, error localization and correction, and examines the related techniques in a comprehensive and original methodological framework. Quality dimension definitions and adopted models are also analyzed in detail, and differences between the proposed solutions are highlighted and discussed. Furthermore, while systematically describing data and information quality as an autonomous research area, paradigms and influences deriving from other areas, such as probability theory, statistical data analysis, data mining, knowledge representation, and machine learning are also included. Last not least, the book also highlights very practical solutions, such as methodologies, benchmarks for the most effective techniques, case studies, and examples. The book has been written primarily for researchers in the fields of databases and information management or in natural sciences who are interested in investigating properties of data and information that have an impact on the quality of experiments, processes and on real life. The material presented is also sufficiently self-contained for masters or PhD-level courses, and it covers all the fundamentals and topics without the need for other textbooks. Data and information system administrators and practitioners, who deal with systems exposed to data-quality issues and as a result need a systematization of the field and practical methods in the area, will also benefit from the combination of concrete practical approaches with sound theoretical formalisms.
Data Quality Management In The Data Age
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Author : Haiyan Yu
language : en
Publisher: Springer Nature
Release Date : 2024-10-29
Data Quality Management In The Data Age written by Haiyan Yu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-29 with Computers categories.
This book addresses data quality management for data markets, including foundational quality issues in modern data science. By clarifying the concept of data quality, its impact on real-world applications, and the challenges stemming from poor data quality, it will equip data scientists and engineers with advanced skills in data quality management, with a particular focus on applications within data markets. This will help them create an environment that encourages potential data sellers with high-quality data to join the market, ultimately leading to an improvement in overall data quality. High-quality data, as a novel factor of production, has assumed a pivotal role in driving digital economic development. The acquisition of such data is particularly important for contemporary decision-making models. Data markets facilitate the procurement of high-quality data and thereby enhance the data supply. Consequently, potential data sellers with high-quality data are incentivized to enter the market, an aspect that is particularly relevant in data-scarce domains such as personalized medicine and services. Data scientists have a pivotal role to play in both the intellectual vitality and the practical utility of high-quality data. Moreover, data quality control presents opportunities for data scientists to engage with less structured or ambiguous problems. The book will foster fruitful discussions on the contributions that various scientists and engineers can make to data quality and the further evolution of data markets.