Meeting The Challenges Of Data Quality Management
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Meeting The Challenges Of Data Quality Management
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Author : Laura Sebastian-Coleman
language : en
Publisher: Academic Press
Release Date : 2022-01-25
Meeting The Challenges Of Data Quality Management written by Laura Sebastian-Coleman and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-25 with Computers categories.
Meeting the Challenges of Data Quality Management outlines the foundational concepts of data quality management and its challenges. The book enables data management professionals to help their organizations get more value from data by addressing the five challenges of data quality management: the meaning challenge (recognizing how data represents reality), the process/quality challenge (creating high-quality data by design), the people challenge (building data literacy), the technical challenge (enabling organizational data to be accessed and used, as well as protected), and the accountability challenge (ensuring organizational leadership treats data as an asset). Organizations that fail to meet these challenges get less value from their data than organizations that address them directly. The book describes core data quality management capabilities and introduces new and experienced DQ practitioners to practical techniques for getting value from activities such as data profiling, DQ monitoring and DQ reporting. It extends these ideas to the management of data quality within big data environments. This book will appeal to data quality and data management professionals, especially those involved with data governance, across a wide range of industries, as well as academic and government organizations. Readership extends to people higher up the organizational ladder (chief data officers, data strategists, analytics leaders) and in different parts of the organization (finance professionals, operations managers, IT leaders) who want to leverage their data and their organizational capabilities (people, processes, technology) to drive value and gain competitive advantage. This will be a key reference for graduate students in computer science programs which normally have a limited focus on the data itself and where data quality management is an often-overlooked aspect of data management courses. Describes the importance of high-quality data to organizations wanting to leverage their data and, more generally, to people living in today’s digitally interconnected world Explores the five challenges in relation to organizational data, including "Big Data," and proposes approaches to meeting them Clarifies how to apply the core capabilities required for an effective data quality management program (data standards definition, data quality assessment, monitoring and reporting, issue management, and improvement) as both stand-alone processes and as integral components of projects and operations Provides Data Quality practitioners with ways to communicate consistently with stakeholders
How Data Can Manage Global Health Pandemics
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Author : Rupa Mahanti
language : en
Publisher: CRC Press
Release Date : 2022-05-08
How Data Can Manage Global Health Pandemics written by Rupa Mahanti and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-08 with Business & Economics categories.
"This book bridges the fields of health care and data to clarify how to use data to manage pandemics. Written while COVID-19 was raging, it identifies both effective practices and misfires, and is grounded in clear, research-based explanations of pandemics and data strategy....The author has written an essential book for students and professionals in both health care and data. While serving the needs of academics and experts, the book is accessible for the general reader." – Eileen Forrester, CEO of Forrester Leadership Group, Author of CMMI for Services, Guidelines for Superior Service "...Rupa Mahanti explores the connections between data and the human response to the spread of disease in her new book,... She recognizes the value of data and the kind of insight it can bring, while at the same time recognizing that using data to solve problems requires not just technology, but also leadership and courage. This is a book for people who want to better understand the role of data and people in solving human problems." -- Laura Sebastian-Coleman, Author of Meeting the Challenges of Data Quality Management In contrast to the 1918 Spanish flu pandemic which occurred in a non-digital age, the timing of the COVID-19 pandemic intersects with the digital age, characterized by the collection of large amounts of data and sophisticated technologies. Data and technology are being used to combat this digital age pandemic in ways that were not possible in the pre-digital age. Given the adverse impacts of pandemics in general and the COVID-19 pandemic in particular, it is imperative that people understand the meaning, origin of pandemics, related terms, trajectory of a new disease, butterfly effect of contagious diseases, factors governing the pandemic potential of a disease, strategies to combat a pandemic, role of data, data sharing, data strategy, data governance, analytics, and data visualization in managing pandemics, pandemic myths, critical success factors in managing pandemics, and lessons learned. How Data Can Manage Global Health Pandemics: Analyzing and Understanding COVID-19 discusses these elements with special reference to COVID-19. Dr. Rupa Mahanti is a business and data consultant and has expertise in different data management disciplines, business process improvement, regulatory reporting, quality management, and more. She is the author of Data Quality (ASQ Quality Press) and the series Data Governance: The Way Forward (Springer).
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.
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.
How To Establish A Data Quality Management Framework
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Author : Accurity
language : en
Publisher: Simplity s.r.o.
Release Date : 2022-05-17
How To Establish A Data Quality Management Framework written by Accurity and has been published by Simplity s.r.o. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-17 with Computers categories.
A significant amount of money is lost every year to bad data. This includes time spent on correcting bad data, evaluating data sources that are not trusted, or simply the costs of mistakes due to incorrect customer identification. Why not improve your business in an area that you can directly influence? Our whitepaper helps you understand the purpose and added value of Data Quality Management, what types of common data quality issues exist, and guides you through the steps needed to establish a good Data Quality Management framework as a part of your overall data governance. In this whitepaper, you will: • Learn what data quality management is and how it helps your business • Understand what data quality is and how you can categorize data issues as data quality dimensions • Discover how bad data is produced in the first place and how to improve data quality • See what position data quality management takes in data governance • Get a step-by-step guide to the data quality management process
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
8th International Conference On Sustainable Commerce Through Ai Uncover The Potential
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Author : M.S. Loganathan
language : en
Publisher: Shanlax Publications
Release Date :
8th International Conference On Sustainable Commerce Through Ai Uncover The Potential written by M.S. Loganathan and has been published by Shanlax Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on with Business & Economics categories.
The conference proceedings of the 8th International Conference on Sustainable Commerce through AI, Crystal-2024, likely include a collection of papers, presentations, and discussions that took place during the event. These proceedings would cover a wide range of topics related to the application of Artificial Intelligence (AI) in Commerce, reflecting the theme of "Unlock the Potential." The proceedings may include Research papers, detailed studies and findings related to AI tools and techniques in various aspects of commerce such as Marketing, Finance, Human Resource, and others. It also include paper presentation summaries of research papers presented at the conference, covering topics like AI applications, case studies, and innovative approaches in commerce. Overall, the conference proceedings would serve as a comprehensive resource for researchers, practitioners, and policymakers interested in understanding the current state and future directions of AI in commerce, providing valuable insights and inspiring further research and collaboration in this field.
Nwqmc National Monitoring Conference 2000 April 25 27 2000 Austin Texas
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Author :
language : en
Publisher:
Release Date : 2000
Nwqmc National Monitoring Conference 2000 April 25 27 2000 Austin Texas written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Water quality categories.
The Semantic Web Trends And Challenges
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Author : Valentina Presutti
language : en
Publisher: Springer
Release Date : 2014-05-09
The Semantic Web Trends And Challenges written by Valentina Presutti and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-09 with Computers categories.
This book constitutes the refereed proceedings of the 11th Extended Semantic Web Conference, ESWC 2014, held in Anissaras, Crete, Greece France, in May 2014. The 50 revised full papers presented together with three invited talks were carefully reviewed and selected from 204 submissions. They are organized in topical sections on mobile, sensor and semantic streams; services, processes and cloud computing; social web and web science; data management; natural language processing; reasoning; machine learning, linked open data; cognition and semantic web; vocabularies, schemas, ontologies. The book also includes 11 papers presented at the PhD Symposium.