Executing Data Quality Projects

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  • Publisher : Academic Press
  • Release : 27 May 2021
  • ISBN : 9780128180167
  • Page : 376 pages
  • Rating : 4.5/5 from 103 voters

Executing Data Quality Projects Book PDF 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

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Executing Data Quality Projects

Executing Data Quality Projects
  • Author : Danette McGilvray
  • Publisher : Academic Press
  • Release Date : 2021-05-27
  • ISBN : 9780128180167
DOWNLOAD 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

Executing Data Quality Projects

Executing Data Quality Projects
  • Author : Danette McGilvray
  • Publisher : Morgan Kaufmann
  • Release Date : 2008
  • ISBN : 0123743699
DOWNLOAD BOOKExecuting Data Quality Projects

Introduces a systematic, effective approach to enhancing and creating data and information quality that integrates a conceptual framework with essential tools, techniques, and instructions, accompanied by helpful templates, real-world examples, and advice, as well as highlighted definitions, key concepts, checkpoints, warnings, communication activities, and best practices. Original. (Intermediate)

The Practitioner's Guide to Data Quality Improvement

The Practitioner's Guide to Data Quality Improvement
  • Author : David Loshin
  • Publisher : Elsevier
  • Release Date : 2010-11-22
  • ISBN : 0080920349
DOWNLOAD 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

Measuring Data Quality for Ongoing Improvement

Measuring Data Quality for Ongoing Improvement
  • Author : Laura Sebastian-Coleman
  • Publisher : Newnes
  • Release Date : 2012-12-31
  • ISBN : 9780123977540
DOWNLOAD 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

Data Quality

Data Quality
  • Author : Jack E. Olson
  • Publisher : Elsevier
  • Release Date : 2003-01-09
  • ISBN : 9780080503691
DOWNLOAD 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.

Data Stewardship

Data Stewardship
  • Author : David Plotkin
  • Publisher : Newnes
  • Release Date : 2013-09-16
  • ISBN : 9780124104457
DOWNLOAD BOOKData Stewardship

Data stewards in business and IT are the backbone of a successful data governance implementation because they do the work to make a company’s data trusted, dependable, and high quality. Data Stewardship explains everything you need to know to successfully implement the stewardship portion of data governance, including how to organize, train, and work with data stewards, get high-quality business definitions and other metadata, and perform the day-to-day tasks using a minimum of the steward’s time and effort.

The Decision Model

The Decision Model
  • Author : Barbara von Halle,Larry Goldberg
  • Publisher : CRC Press
  • Release Date : 2009-10-27
  • ISBN : 1420082825
DOWNLOAD BOOKThe Decision Model

In the current fast-paced and constantly changing business environment, it is more important than ever for organizations to be agile, monitor business performance, and meet with increasingly stringent compliance requirements. Written by pioneering consultants and bestselling authors with track records of international success, The Decision Model: A Business Logic Framework Linking Business and Technology provides a platform for rethinking how to view, design, execute, and govern business logic. The book explains how to implement the Decision Model, a stable, rigorous

Journey to Data Quality

Journey to Data Quality
  • Author : Yang W. Lee,Leo L. Pipino,James D. Funk,Richard Y. Wang
  • Publisher : Mit Press
  • Release Date : 2006
  • ISBN : UOM:49015003152734
DOWNLOAD BOOKJourney to Data Quality

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 Quality offers 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,

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 Date : 2021-08-01
  • ISBN : 9781628256888
DOWNLOAD 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

Predictive Analytics For Dummies

Predictive Analytics For Dummies
  • Author : Dr. Anasse Bari,Mohamed Chaouchi,Tommy Jung
  • Publisher : John Wiley & Sons
  • Release Date : 2014-03-06
  • ISBN : 9781118729410
DOWNLOAD BOOKPredictive Analytics For Dummies

Combine business sense, statistics, and computers in a new and intuitive way, thanks to Big Data Predictive analytics is a branch of data mining that helps predict probabilities and trends. Predictive Analytics For Dummies explores the power of predictive analytics and how you can use it to make valuable predictions for your business, or in fields such as advertising, fraud detection, politics, and others. This practical book does not bog you down with loads of mathematical or scientific theory, but

MASTER DATA MANAGEMENT AND DATA GOVERNANCE, 2/E

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  • Publisher : McGraw Hill Professional
  • Release Date : 2010-12-06
  • ISBN : 9780071744591
DOWNLOAD BOOKMASTER DATA MANAGEMENT AND DATA GOVERNANCE, 2/E

The latest techniques for building a customer-focused enterprise environment "The authors have appreciated that MDM is a complex multidimensional area, and have set out to cover each of these dimensions in sufficient detail to provide adequate practical guidance to anyone implementing MDM. While this necessarily makes the book rather long, it means that the authors achieve a comprehensive treatment of MDM that is lacking in previous works." -- Malcolm Chisholm, Ph.D., President, AskGet.com Consulting, Inc. Regain control of

Data Quality Assessment

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  • Author : Arkady Maydanchik
  • Publisher : Technics Publications
  • Release Date : 2007-04-01
  • ISBN : 9781634620475
DOWNLOAD 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

Data Quality

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  • Author : Rupa Mahanti
  • Publisher : Quality Press
  • Release Date : 2019-03-18
  • ISBN : 9780873899772
DOWNLOAD 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

Ten Steps to a Results-Based Monitoring and Evaluation System

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  • Author : Jody Zall Kusek,Ray C. Rist
  • Publisher : World Bank Publications
  • Release Date : 2004-06-15
  • ISBN : 9780821389072
DOWNLOAD 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.

Python for Data Analysis

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  • Author : Wes McKinney
  • Publisher : "O'Reilly Media, Inc."
  • Release Date : 2017-09-25
  • ISBN : 9781491957615
DOWNLOAD BOOKPython for Data Analysis

Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in