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Executing Data Quality Projects

Executing Data Quality Projects
  • Author : Danette McGilvray
  • Publsiher : Academic Press
  • Release : 27 May 2021
  • ISBN : 0128180161
  • Pages : 376 pages
  • Rating : 4/5 from 21 ratings
GET THIS BOOKExecuting Data Quality Projects

Summary:
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


Executing Data Quality Projects

Executing Data Quality Projects
  • Author : Danette McGilvray
  • Publisher : Academic Press
  • Release : 27 May 2021
GET THIS BOOKExecuting Data Quality Projects

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

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Executing Data Quality Projects

Executing Data Quality Projects
  • Author : Danette McGilvray
  • Publisher : Elsevier
  • Release : 01 September 2008
GET THIS BOOKExecuting Data Quality Projects

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

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The Practitioner's Guide to Data Quality Improvement

The Practitioner's Guide to Data Quality Improvement
  • Author : David Loshin
  • Publisher : Elsevier
  • Release : 22 November 2010
GET THIS BOOKThe Practitioner's Guide to Data Quality Improvement

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

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Data Quality Assessment

Data Quality Assessment
  • Author : Arkady Maydanchik
  • Publisher : Technics Publications
  • Release : 01 April 2007
GET THIS BOOKData Quality Assessment

Imagine a group of prehistoric hunters armed with stone-tipped spears. Their primitive weapons made hunting large animals, such as mammoths, dangerous work. Over time, however, a new breed of hunters developed. They would stretch the skin of a previously killed mammoth on the wall and throw their spears, while observing which spear, thrown from which angle and distance, penetrated the skin the best. The data gathered helped them make better spears and develop better hunting strategies. Quality data is the

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Measuring Data Quality for Ongoing Improvement

Measuring Data Quality for Ongoing Improvement
  • Author : Laura Sebastian-Coleman
  • Publisher : Newnes
  • Release : 31 December 2012
GET THIS BOOKMeasuring Data Quality for Ongoing Improvement

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

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Data Quality

Data Quality
  • Author : Jack E. Olson
  • Publisher : Elsevier
  • Release : 09 January 2003
GET THIS BOOKData Quality

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.

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Data Driven

Data Driven
  • Author : Thomas C. Redman
  • Publisher : Harvard Business Press
  • Release : 22 September 2008
GET THIS BOOKData Driven

Your company's data has the potential to add enormous value to every facet of the organization -- from marketing and new product development to strategy to financial management. Yet if your company is like most, it's not using its data to create strategic advantage. Data sits around unused -- or incorrect data fouls up operations and decision making. In Data Driven, Thomas Redman, the "Data Doc," shows how to leverage and deploy data to sharpen your company's competitive edge and

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A Guide to the Project Management Body of Knowledge (PMBOK® Guide) – Seventh Edition and The Standard for Project Management (BRAZILIAN PORTUGUESE)

A Guide to the Project Management Body of Knowledge (PMBOK® Guide) – Seventh Edition and The Standard for Project Management (BRAZILIAN PORTUGUESE)
  • Author : Project Management Institute Project Management Institute
  • Publisher : Project Management Institute
  • Release : 01 August 2021
GET THIS BOOKA Guide to the Project Management Body of Knowledge (PMBOK® Guide) – Seventh Edition and The Standard for Project Management (BRAZILIAN PORTUGUESE)

PMBOK&® Guide is the go-to resource for project management practitioners. The project management profession has significantly evolved due to emerging technology, new approaches and rapid market changes. Reflecting this evolution, The Standard for Project Management enumerates 12 principles of project management and the PMBOK&® Guide &– Seventh Edition is structured around eight project performance domains.This edition is designed to address practitioners' current and future needs and to help them be more proactive, innovative and nimble in enabling desired project outcomes.This

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Agile Approaches for Successfully Managing and Executing Projects in the Fourth Industrial Revolution

Agile Approaches for Successfully Managing and Executing Projects in the Fourth Industrial Revolution
  • Author : Bolat, Hür Bersam,Temur, Gül Tekin
  • Publisher : IGI Global
  • Release : 15 March 2019
GET THIS BOOKAgile Approaches for Successfully Managing and Executing Projects in the Fourth Industrial Revolution

Communication between man and machine is vital to completing projects in the current day and age. Without this constant connectiveness as we enter an era of big data, project completion will result in utter failure. Agile Approaches for Successfully Managing and Executing Projects in the Fourth Industrial Revolution addresses changes wrought by Industry 4.0 and its effects on project management as well as adaptations and adjustments that will need to be made within project life cycles and project risk management. Highlighting

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Data Quality

Data Quality
  • Author : Rupa Mahanti
  • Publisher : Quality Press
  • Release : 18 March 2019
GET THIS BOOKData Quality

“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” Good data is a source of myriad

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Telling Your Data Story

Telling Your Data Story
  • Author : Scott Taylor
  • Publisher : Anonim
  • Release : 15 November 2020
GET THIS BOOKTelling Your Data Story

The Data Whisperer's practical guide to explaining and understanding the strategic value of data management. The need for data management is everywhere across your company. The value of every digitally transformative customer-facing initiative, every data science and analytics-based project, every as-a-service offering, every foray into e-commerce, and every enterprise software implementation is inextricably linked to the successful output of data management efforts. Although it is a simple function of garbage in garbage out, that slogan rarely drives any sustainable executive

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Managing Data Quality

Managing Data Quality
  • Author : Tim King,Julian Schwarzenbach
  • Publisher : BCS, The Chartered Institute for IT
  • Release : 27 April 2020
GET THIS BOOKManaging Data Quality

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.

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Entity Resolution and Information Quality

Entity Resolution and Information Quality
  • Author : John R. Talburt
  • Publisher : Elsevier
  • Release : 14 January 2011
GET THIS BOOKEntity Resolution and Information Quality

Entity Resolution and Information Quality presents topics and definitions, and clarifies confusing terminologies regarding entity resolution and information quality. It takes a very wide view of IQ, including its six-domain framework and the skills formed by the International Association for Information and Data Quality {IAIDQ). The book includes chapters that cover the principles of entity resolution and the principles of Information Quality, in addition to their concepts and terminology. It also discusses the Fellegi-Sunter theory of record linkage, the Stanford

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Ten Steps to a Results-Based Monitoring and Evaluation System

Ten Steps to a Results-Based Monitoring and Evaluation System
  • Author : Jody Zall Kusek,Ray C. Rist
  • Publisher : World Bank Publications
  • Release : 15 June 2004
GET THIS BOOKTen Steps to a Results-Based Monitoring and Evaluation System

This Handbook provides a comprehensive ten-step model that will help guide development practitioners through the process of designing and building a results-based monitoring and evaluation system.

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Getting in Front on Data

Getting in Front on Data
  • Author : Thomas C. Redman, Ph.D.
  • Publisher : Technics Publications
  • Release : 12 September 2016
GET THIS BOOKGetting in Front on Data

This is the single best book ever written on data quality. Clear, concise, and actionable. We all want to leverage our data resources to drive growth, but we too often ignore the fundamentals of data quality, which almost always inhibits our success. Tom lays out a clear path for each organization to holistically improve not only its data quality, but more importantly the performance of its business as a whole. —Jeffrey G. McMillan, Chief Analytics and Data Officer, Morgan Stanley

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