Data Integrity And Quality
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Data Integrity And Data Governance
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Author : R. D. McDowall
language : en
Publisher: Royal Society of Chemistry
Release Date : 2018-11-09
Data Integrity And Data Governance written by R. D. McDowall and has been published by Royal Society of Chemistry this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-09 with Computers categories.
This book provides practical and detailed advice on how to implement data governance and data integrity for regulated analytical laboratories working in the pharmaceutical and allied industries.
Data Integrity And Quality
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Author : Santhosh Kumar Balan
language : en
Publisher: BoD – Books on Demand
Release Date : 2021-06-23
Data Integrity And Quality written by Santhosh Kumar Balan and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-23 with Computers categories.
Data integrity is the quality, reliability, trustworthiness, and completeness of a data set, providing accuracy, consistency, and context. Data quality refers to the state of qualitative or quantitative pieces of information. Over five sections, this book discusses data integrity and data quality as well as their applications in various fields.
Site Reliability Engineering
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Author : Niall Richard Murphy
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-03-23
Site Reliability Engineering written by Niall Richard Murphy 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 2016-03-23 with Computers categories.
The overwhelming majority of a software systemâ??s lifespan is spent in use, not in design or implementation. So, why does conventional wisdom insist that software engineers focus primarily on the design and development of large-scale computing systems? In this collection of essays and articles, key members of Googleâ??s Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world. Youâ??ll learn the principles and practices that enable Google engineers to make systems more scalable, reliable, and efficientâ??lessons directly applicable to your organization. This book is divided into four sections: Introductionâ??Learn what site reliability engineering is and why it differs from conventional IT industry practices Principlesâ??Examine the patterns, behaviors, and areas of concern that influence the work of a site reliability engineer (SRE) Practicesâ??Understand the theory and practice of an SREâ??s day-to-day work: building and operating large distributed computing systems Managementâ??Explore Google's best practices for training, communication, and meetings that your organization can use
Database Integrity Challenges And Solutions
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Author : Doorn, Jorge Horacio
language : en
Publisher: IGI Global
Release Date : 2001-07-01
Database Integrity Challenges And Solutions written by Doorn, Jorge Horacio and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-07-01 with Computers categories.
Geared toward designers and professionals interested in the conceptual aspects of integrity problems in different paradigms, Database Integrity: Challenges and Solutions successfully addresses these and a variety of other issues.
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
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 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
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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.
Method Validation In Pharmaceutical Analysis
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Author : Joachim Ermer
language : en
Publisher: John Wiley & Sons
Release Date : 2025-05-27
Method Validation In Pharmaceutical Analysis written by Joachim Ermer 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 2025-05-27 with Medical categories.
New edition of the gold standard in the field of pharmaceutical analysis, extensively updated to include the new ICH Guidelines Q2 and Q14 Following an all-encompassing lifecycle approach to analytical procedures in pharmaceutical analysis, Method Validation in Pharmaceutical Analysis provides hands-on information for readers involved in development, validation, and continued maintenance and evaluation of analytical procedures in pharmaceutical analysis. This newly revised and updated Third Edition includes much-needed interpretation of the most recent ICH guidelines for validation and method development, as well as recent publications of the USP Validation & Verification Expert Panel on Analytical Procedure Lifecycle Management and the activities of the British Pharmacopeia AQbD Working Party. It also addresses trending topics in the field such as data integrity and continuous monitoring of analytical performance. Written by a team of highly qualified pharmaceutical professionals, Method Validation in Pharmaceutical Analysis includes information on sample topics such as: Data governance, data integrity, and data quality, as well as analytical instrument qualification and system validation lifecycle Continued HPLC performance qualification, analytical target profile, decision rules and fitness for intended use, and performance characteristics of analytical procedures Method selection, development, and optimization, multivariate analytical procedures, and risk assessment and analytical control strategy Implementation of compendial/pharmacopeia test procedures, transfer of analytical procedures, and the lifecycle approach to transfer of analytical procedures Completely comprehensive in coverage, Method Validation in Pharmaceutical Analysis is an essential reference for scientists, researchers, and professionals in the pharmaceutical industry, analytical chemists, QA officers, and public authorities tasked with relevant regulatory responsibilities.