Getting in Front on Data, by Tom Redman
This book lays out the roles everyone, up and down the organization chart, can and must play to ensure that data is up to the demands of its use, in day-in, day-out work, decision-making, planning, and analytics.
Why?
How and Who?
When?
In Summary
Do I Have a Data Quality Problem?
The Wrong Reaction in the Face of Bad Data
Use the Rule of Ten to Estimate Costs
Identify “Hard-to-Quantify” Costs of Special Importance
Think Longer-Term
So What’s in It for Me?
In Summary
Recognize That You Are a Data Customer
Communicate Your Needs
Innovate and Encourage Innovation
Actively Manage Both Internal and External Suppliers
Make Your Hidden Data Factories Explicit and Efficient
Build Organizational Capability
In Summary
Recognize You Are a Data Creator and That Your Work Impacts Others
Focus on the Most Important Needs of the Most Important Customers
Measure Quality Against Those Needs, in the Eyes of the Customers
Find and Eliminate Root Causes of Error
Establish Control
Innovate, Innovate, Innovate
In Summary
Manage Data Creation as a Process
Clarify Managerial Responsibilities
Extend the Voice of the Customer
Look for Improvement Opportunities on the Interfaces Between Tasks/Steps
Build Organizational Capabilities
Employ Embedded Data Managers
The Fundamental Organization Unit for Data Quality
Special Instructions for Creating Common Data Definitions
In Summary
Provocateurs Look to Improve Their Current Work
Provocateurs Dig Deeper
Provocateurs Achieve a Real Result
Provocateurs Are Not Rabble Rousers
Provocateurs Have Courage and Judgment
In Summary
Pay Special Attention to Proprietary Data
Focus the Effort
Engage Senior Management
Connect Data Creators and Data Customers
Provide Common Functions Where It Makes Sense
Own the Data Definition Processes
Actively Manage Change
Build Small but Powerful Core Data Quality Teams
In Summary
Understand the Business Case
Put the Right People and Structure in Place
Insist that the Organization Get in Front on Data Quality
Engage Visibly
In Summary
Store, Move, and Deliver Data Safely and Securely
Automate Data Translation as Data Moves From System to System
Contribute to the DQ Effort
Don’t Take Overall Responsibility for Data Quality
Use Business Data Definitions in Systems Development
Reduce Data Translation by Simplifying the Data Architecture
Put in Place a Powerful Team to Support Data Quality
In Summary
Improving Access Bill Quality at AT&T
Data Definitions That Stand the Test of Time at Aera Energy
In Summary
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
This book lays out the roles everyone, up and down the organization chart, can and must play to ensure that data is up to the demands of its use, in day-in, day-out work, decision-making, planning, and analytics.
By now, everyone knows that bad data extorts an enormous toll, adding huge (though often hidden) costs, and making it more difficult to make good decisions and leverage advanced analyses. While the problems are pervasive and insidious, they are also solvable! As Tom Redman, “the Data Doc,” explains in Getting in Front on Data, the secret lies in getting the right people in the right roles to “get in front” of the management and social issues that lead to bad data in the first place.
Everyone should see himself or herself in this book. We are all both data customers and data creators–Getting in Front on Data proposes new roles for data professionals as:
Data quality has always been important. But now, in the growing digital economy where business transactions and customer experiences are automated and tailored, data quality is critical. This book comes just in time.
–Maria C. Villar, Global Vice President, SAP America, Inc.
Winning, and more importantly thriving, in the digital age requires more than stating “Data is a strategic corporate asset.” Leaders and organizations need a plan of action to make the new vision a reality. Tom’s latest book is a how-to for those seeking that reality.
–Bob Palermo, Vice President, Performance Excellence, Shell Unconventionals
Many, if not most, companies still struggle with their data. With his latest offering, Tom Redman sets out a path they can follow to Get in Front on Data. Based on his decades of experience working with many companies and individuals, this is the most practical guide around. A must read for data professionals, and especially data “provocateurs”.
–Ken Self, President IAIDQ
This book offers a unique perspective on how to think about data and address Data Quality – offering practical guidance and useful instruction from the perspective of each stakeholder. The process–and processes–to go from business need to having the right quality data to address that need is no small task.
–John Nicodemo, Global Leader, Data Quality, Dun & Bradstreet
Getting in Front on Data is a clearly written survival handbook for the new data-driven economy. It is a “must read” for the employees of any organization expecting to remain relevant and competitive. The “Data Doc” has an extraordinary talent for explaining key concepts with simple examples and understandable analogies making it accessible to everyone in their organization regardless of their role.
–John R. Talburt, Director of the Information Quality Graduate Program University of Arkansas at Little Rock
Tom Redman, the Data Doc, and his company, Data Quality Solutions, help leaders world-wide attack data quality head-on. Thousands benefit from his approaches and methods, which focus on getting the right people in the right roles, creating data correctly the first time, and addressing the issues that lead to bad data. Tom started his career at Bell Labs, where he conceived and led the Data Quality Lab. He was first to understand the fundamental importance of data and data quality, understand the nature of data in organizations, and give meaning to the phrase “manage data assets.” He has a Ph.D. in Statistics and two patents. Tom and his wife Nancy live in Rumson, New Jersey, USA.
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