Data Stewardship. An Actionable Guide to Effective Data Management and Data Governance

231 Pages·2014·5.16 MB·English

by  David Plotkin (Auth.)

DATA STEWARDSHIP
Data Stewardship
An Actionable Guide to Effective
Data Management and Data Governance
David Plotkin
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Notices
Knowledge and best practice in this field are constantly changing. As new research and experience
broaden our understanding, changes in research methods or professional practices, may become necessary.
Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using
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Library of Congress Cataloging-in-Publication Data
Plotkin, David.
Data stewardship : an actionable guide to effective data management and data governance/David Plotkin.
pages cm.
Includes bibliographical references and index.
ISBN 978-0-12-410389-4 (alk. paper)
1. Information technology–Security measures. 2. Data protection.
3. Data warehousing. I. Title.
QA76.9.A25P594 2014
658.4′0380285574–dc23
2013026961
British Library Cataloguing-in-Publication Data
A catalogue record for this book is available from the British Library.
ISBN: 978-0-12-410389-4
Printed and bound in the United States of America
14 15 16 17 18 10 9 8 7 6 5 4 3 2 1
For information on all MK publications
visit our website at www.mkp.com
This book is for my beloved Jo-Rita. She brought peace, strength, love, joy,
and balance back into my life. Without her, this book never would have been written,
and my life would be a very lonely place. With her, all is well, and life is good.
In praise of Data Stewardship: An Actionable Guide to
Effective Data Management and Data Governance
“The volume, velocity and variety of data is overwhelming every company.
Governing this strategic asset effectively and efficiently is a business impera-
tive. In this book, David Plotkin, an experienced data practitioner with doz-
ens of implementations under his belt, provides a comprehensive view of
Data Governance and practical steps required to implement a strong data
governance program. It can be used as a guide, if you are launching a new
data governance program, are adjusting an existing program to improve per-
formance or are interested in learning about data governance.”
—Jay Zaidi, Enterprise Data Management Leader, Fannie Mae
“David Plotkin has delivered a practical, readable, ‘jump-in-anywhere’
book that demystifies the gentle art of Data Stewardship.”
—Gwen Thomas, Founder, The Data Governance Institute
vii
Acknowledgments
A book is the labor of many people. I want to thank my acquisitions edi-
tor, Andrea Dierna, for helping me lay out what the book would cover, and
then hounding me until I agreed to write it. I also want to thank Heather
Scherer, who shepherded the manuscript through editing and production,
and was endlessly patient. In addition, I would like to thank the copyeditor,
Jodie Allen who made sure that everything was shipshape, grammatically
correct, and consistent and the project manager, Punitha for her work.
This book had three reviewers: Danette McGilvray, Laura Sebastian-
Coleman, and Dagna Gaythorpe. They were invaluable in ensuring that
the topics “hung together,” made sense, and didn’t leave out anything
important. These three are all good friends, and remain so after the editing
(grin). Laura is an ex-English teacher, and she made sure that my grammar
and sentence structure made for easy reading. And that made me a better
writer, so I am especially grateful to her for the massive effort she put into
this book.
Lastly, there are a group of people who never seem to get acknowledged,
but should be. Down through the years, I have held a string of really good
jobs, each one building on the last. I have gained experience as a practi-
tioner, and have been able to share that experience with others through
conferences. So, I want to thank the people who hired me into those jobs,
believed that I knew enough to perform them, and that I could learn what
was needed to be successful. These folks include Lee Klein (InPower and
Longs Drugstores), Brian Kilcourse (Longs Drugstores), David Harberson
(Wells Fargo), Ralph Blore (CSAA, which became AAA NCNU), George
Acosta (Bank of America), and Martha Dember and Joe Dossantos (EMC
Consulting).
Finally, I especially want to acknowledge Tony Shaw of Dataversity, who
has had me back again and again to attend and speak at their conferences,
and has even allowed me to attend for free when I was between jobs and
couldn’t afford the registration. Thanks so much, old chap!
xv
About the Author
David Plotkin is an advisory consultant for EMC2, working in enterprise
information management. He is responsible for leading efforts at client
companies to plan and implement Data Governance both as standalone
efforts and as part of other initiatives such as data quality improvement and
Master Data Management. He has previously managed Data Governance
at an insurance company and managed data quality at two large banks. He
has been working with Data Governance, data modeling, metadata, and
data quality for over 20 years. He is a popular speaker at DAMA chap-
ters and conferences, and serves as a subject-matter expert on many topics
around metadata, Data Governance, and data quality.
xvii
Foreword
David Plotkin is a practical man. Over the years, we’ve had many conver-
sations about Data Governance and Stewardship models, concepts, activi-
ties, and processes. Nearly every one of those conversations has included
a point where David would pause, take a deep breath, and flash his big
smile. “Uh oh,” I would think. “Here it comes.” And my friend would
never disappoint. “Good ideas, Gwen,” he’d say. “Now how do I put them
into practice?” Or, sometimes, “Here’s how I’ve already put a version of
that into practice with my teams.”
Getting the right things done, in the right way—that’s a goal David and I
have always agreed on. But, the role of Data Stewards in an organization?
That’s different. “There’s no single right model!” I would insist, citing
examples of organizations that had successfully positioned Data Stewards
as point-of-entry data perfectionists, with little organizational clout.
“But those organizations also had people who made data decisions, right?”
David would ask, and I would have to agree. “And councils? Negotiators?
People who interpreted between business users of information and technol-
ogy teams? Rule makers? Rule interpreters? People to address data issues?
People who made sure that the right things got done in the right way?”
Of course, I would always agree. Yes, these types of roles—no matter
what they’re called—are critical in modern, data-driven organizations.
Taking care of data requires motivated, skilled people at all levels of the
organization.
“Yes, it does!” David would say, his eyes twinkling. “And do you know
what they need? Guidelines, logical grouping of responsibilities, lists of
activities they should undertake, and descriptions of what details to include
so they can be successful, whatever their job titles.”
Of course, my friend was right. Someone needed to collect this informa-
tion into a practical, readable, “jump-in-anywhere” book that would help
motivated, bright people become skilled at the art of Data Stewardship.
And that’s what my practical friend David has done. Bravo!
Gwen Thomas
Founder, The Data Governance Institute
xix
Introduction
Companies are getting serious about managing their data, including
improving data quality, understanding the meaning of the data, lever-
aging the data for competitive advantage, and treating data as the enter-
prise asset it should be. But doing a proper job of managing data requires
accountability—that is, business functions must take responsibility for the
data they own and use. The formal recognition of the need to have a struc-
ture, organization, and resources in place to manage data—and the actual
implementation of that need—has come to be known as Data Governance.
Within the umbrella of Data Governance is Data Stewardship. Various
kinds of Data Stewards (detailed later in the book) work closely with the
data as well as other subject-matter experts and stakeholders to achieve the
goals and deliverables laid out by the Data Governance effort. The Data
Stewardship efforts are managed and coordinated by the Data Governance
Program Office and supported by high-ranking officers of the company.
This book provides usable and actionable information and instructions on
how to set up and run a Data Stewardship effort within Data Governance.
The book is designed to provide everything a new Data Steward or Data
Governance Manager needs to be effective and efficient when it comes to
Data Stewardship. It also provides the details needed by those taking on
the responsibilities of a Data Steward.
PROBLEM STATEMENT
There are many challenges that must be faced when working with data,
including:
■ Data doesn’t explain itself. Someone must provide an interpretation
of the data, including what it means, how to use it properly, and how to
evaluate whether the data is of good quality or not.
■ Data is shared and used by many, for many different purposes.
So who owns it? Who makes decisions about it and is responsible when
the data goes “wrong”?
■ Many processes that use data depend on people upstream of the
process to “get it right.” But who says what “right” is? And who
determines when it goes “wrong”?
■ The software development life cycles require many handoffs
between requirements, analysis, design, construction, and data use.
There are lots of places where the handoffs can corrupt the data and
endanger the data quality.
xxi
xxii INTRODUCTION
■ Technical people tasked with data implementation are not familiar
with the data’s meaning or how it is used.
■ Those of us in the data community have a long history and habits
around tolerance of ambiguity both in data meaning and data
content.
All of these factors lead to a poor understanding of the data and a percep-
tion of poor quality, with little ability to know the difference. The answer
to these challenges is that data needs to be actively and efficiently man-
aged. Keep in mind too that the rather haphazard “methodology” used by
many companies to collect metadata does not represent true or effective
data management. Some of the failures include:
■ Data definitions: These are often written in haste by project staff
(if they are written at all), and the definitions are not rationalized
across the enterprise, leading to multiple definitions of the same term,
often under different data element names.
■ Data quality: The data quality rules are often not defined and the
quality itself is rarely measured. Even when the rules are defined,
the context for the rule (the data usage for which the rules applies) is
often ignored. All of this leads to confusion about what data quality is
required, as well as what data quality is achieved.
■ Documentation: Documents containing metadata are rarely
officially published, and are often lost, tucked away on shelves or in
archived files. The documentation is not widely and easily available,
nor is there a robust search engine so that interested users can find
what they need.
■ Creation and usage business rules: There is often a lack of
understanding about the conditions under which an entity (such as
customer or product) can or should be created, as well as how data
should be used. This lack of understanding leads to incomplete or
inaccurate information being collected about the entity, as well as
data being used for purposes for which it was never intended. The
end result is that business decisions based on the data may lead to
suboptimal results.
Formal enterprise-wide Data Stewardship, as part of a Data Governance
effort, is crucial in managing data and achieving solutions to these chal-
lenges. With Data Stewardship, the organization can begin treating data
as an asset. Like other assets, the data needs to be inventoried, owned,
used wisely, and understood. This requires different techniques with data
than with physical assets, but the need is the same. With the data asset,
inventorying and understanding the data takes the form of a formally pub-
lished business glossary, often in conjunction with a metadata repository.