Executing data quality projects : ten steps to quality data and trusted information / Danette McGilvray.

Format:

Book

Author/Creator:

McGilvray, Danette, author.

Language:

English

Subjects (All):

Information technology--Management.

Information technology.

Electronic data processing--Quality control.

Electronic data processing.

Physical Description:

1 online resource (378 pages)

Edition:

2nd ed.

Place of Publication:

London, England : Academic Press, [2021]

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.

Contents:

Intro

Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information (TM)

Copyright

In Praise Of

Dedication

Contents

Acknowledgments

Foreword

Introduction

The Reason for This Book

What Is in This Book

Intended Audiences and How to Use This Book

Why a Second Edition

My Goals for You

Get Started!

Structure of This Book

Chapter 1 Data Quality and the Data-Dependent World

Data, Data Everywhere

Trends and the Need for High-Quality Data

Data and Information - Assets to Be Managed

The Leader's Data Manifesto

What You Can Do

Are You Ready to Change?

Chapter 2 Data Quality in Action

Introduction to Chapter 2

A Word About Tools

Real Issues Need Real Solutions

About the Ten Steps Methodology

The Data in Action Triangle

Preparing Your People

Engaging Management

Key Terms

Chapter 2 Summary

Chapter 3 Key Concepts

Introduction to Chapter 3

The Framework for Information Quality

The Information Life Cycle

Data Quality Dimensions

Business Impact Techniques

Data Categories

Data Specifications

Data Governance and Stewardship

Ten Steps Process Overview

Data Quality Improvement Cycle

Concepts and Action - Making the Connection

Chapter 3 Summary

Chapter 4 The Ten Steps Process

Introduction to Chapter 4

Step 1 Determine Business Needs and Approach

Introduction to Step 1

Step 1.1 Prioritize Business Needs and Select Project Focus

Business Benefit and Context

Approach

Sample Output and Templates

Step 1.2 Plan the Project

Step 1 Summary

Step 2 Analyze Information Environment

Introduction to Step 2

Step 2.1 Understand Relevant Requirements and Constraints

Approach.

Sample Output and Templates

Step 2.2 Understand Relevant Data and Data Specifications

Step 2.3 Understand Relevant Technology

Step 2.4 Understand Relevant Processes

Step 2.5 Understand Relevant People and Organizations

Step 2.6 Understand Relevant Information Life Cycle

Step 2 Summary

Step 3 Assess Data Quality

Introduction to Step 3

Step 3.1 Perception of Relevance and Trust

Step 3.2 Data Specifications

Step 3.3 Data Integrity Fundamentals

Step 3.4 Accuracy

Step 3.5 Uniqueness and Deduplication

Step 3.6 Consistency and Synchronization

Step 3.7 Timeliness

Step 3.8 Access

Step 3.9 Security and Privacy

Step 3.10 Presentation Quality

Step 3.11 Data Coverage

Business Benefit and Context.

Approach

Step 3.12 Data Decay

Step 3.13 Usability and Transactability

Step 3.14 Other Relevant Data Quality Dimensions

Step 3 Summary

Step 4 Assess Business Impact

Introduction to Step 4

Step 4.1 Anecdotes

Step 4.2 Connect the Dots

Step 4.3 Usage

Step 4.4 Five Whys for Business Impact

Step 4.5 Process Impact

Step 4.6 Risk Analysis

Step 4.7 Perception of Relevance and Trust

Step 4.8 Benefit vs. Cost Matrix

Step 4.9 Ranking and Prioritization

Step 4.10 Cost of Low-Quality Data

Step 4.11 Cost-Benefit Analysis and ROI

Step 4.12 Other Relevant Business Impact Techniques

Step 4 Summary

Step 5 Identify Root Causes

Introduction to Step 5.

Step 5.1 Five Whys for Root Causes

Step 5.2 Track and Trace

Step 5.3 Cause-and-Effect/Fishbone Diagram

Step 5.4 Other Relevant Root Cause Analysis Techniques

Step 5 Summary

Step 6 Develop Improvement Plans

Step 6 Summary

Step 7 Prevent Future Data Errors

Step 7 Summary

Step 8 Correct Current Data Errors

Step 8 Summary

Step 9 Monitor Controls

Step 9 Summary

Step 10 Communicate, Manage, and Engage People Throughout

Step 10 Summary

Chapter 4 Summary

Chapter 5 Structuring Your Project

Introduction to Chapter 5

Types of Data Quality Projects

Project Objectives

Comparing SDLCs

Data Quality and Governance in SDLCs

Roles in Data Quality Projects

Project Timing, Communication, and Engagement

Chapter 5 Summary

Chapter 6 Other Techniques and Tools

Introduction to Chapter 6

Track Issues and Action Items

Design Data Capture and Assessment Plans

Analyze, Synthesize, Recommend, Document, and Act on Results

Information Life Cycle Approaches

Conduct a Survey

Metrics

The Ten Steps and Other Methodologies and Standards

Tools for Managing Data Quality

Chapter 6 Summary

Chapter 7 A Few Final Words

Appendix: Quick References.

Framework for Information Quality

POSMAD Interaction Matrix Detail

The Ten Steps Process

Process Flows for Steps 1-4

Data in Action Triangle

Glossary

List of Figures, Tables, and Templates

Bibliography

Index

About the Author.

Notes:

Description based on print version record.

ISBN:

9780128180167

0128180161

OCLC:

1253132410