Getting in Front on Data: Who Does What
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--after all, we use data created by others and create data used by others. And all of us must step up to these roles. As data customers, we must clarify our most important needs and communicate them to data creators. As data creators, we must strive to meet those needs by finding and eliminating the root causes of error.
Getting in Front on Data proposes new roles for data professionals as:
- embedded data managers, in helping data customers and creators complete their work,
- DQ team leads, in connecting customers and creators, pulling the entire program together, and training people on their new roles,
- data maestros, in providing deep expertise on the really tough problems,
- chief data architects, in establishing common data definitions, and
- technologists, in increasing scale and decreasing unit cost.
Getting in Front on Data introduces a new role, the data provocateur, the motive force in attacking data quality properly! This book urges everyone to unleash their inner provocateur.
Finally, it crystallizes what senior leaders must do if their entire organizations are to enjoy the benefits of high-quality 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
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
From Tom Davenport's foreword:
Instead of engineering, Redman realized in his data quality work with companies that people were both the cause of and the solution to data quality problems. Instead of advocating for abstract data architectures, he argues for very tangible organizational architectures. Since he knows that data quality issues are inextricably bound with business processes and organizational structures, he also knows that to address those problems, you have to work with the people who own those processes and structures.
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