Executing Data Quality Projects TEN STEPS to Quality Data and Trusted Information
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Download the following files to provide easy references to
important concepts and provide templates for jumpstarting
your information quality work.
Content Highlights:
- Includes numerous templates, detailed examples, and practical advice for executing every step of
The Ten Steps approach.
- Allows for quick reference with an easy-to-use format highlighting key concepts and definitions,
important checkpoints, communication activities, and best practices.

Danette McGilvray is
president and principal of
Granite Falls Consulting.
For more than ten years she
led information quality
initiatives at Hewlett-
Packard and Agilent
Technologies. In her roles
as practitioner, program
and project manager, and
internal consultant, she
gained firsthand experience
in implementing data
quality in projects. She saw
the benefits resulting from a
focus on information quality
in addition to the chal-
lenges and opportunities.
As principal consultant for
Granite Falls, she continues
to use her expertise to help
clients in many industries.
She recognized those ideas
common to all data and all
types and sizes of organi-
zations. This, along with her
previous experience, led
her to develop The Ten
Steps methodology—a
practical and flexible
approach that combines
concepts with realistic how-
to advice.
Learn more about Danette.


About the Book
In today’s world of instant global communication and trends that
turn on a dime, up-to-date and reliable information is essential to
effective competition.
Executing Data Quality Projects: Ten Steps to Quality Data and
Trusted Information™, provides a systematic approach for improving
and creating data and information quality within any organization. It
explains a methodology that combines a conceptual framework for
understanding information quality with the techniques, tools, and
instructions for improving and creating information quality.
Every company is different, yet the underlying approach to data
quality described in the book applies to all types of data, whether
finance, research, development, procurement, manufacturing, sales
and marketing, order management, human resources, and so on. It
applies to numerous types of organizations—businesses and
corporations of all sizes, educational institutions, government
agencies, and nonprofit and charitable organizations—because all
depend on information to succeed.
ADOBE READER
is available here...
The Quick References are described in the book in Chapter 2 Key Concepts and are summarized in an at-a-glance format in the Appendix Quick References.
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The templates provide a starting point to create your own forms and documents. See the book for additional information to help you use the templates such as descriptions, examples, and how and where to use them.
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Additional resources provide links to related information that can support your data quality goals and personal career development.
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"Danette's book takes a
pragmatic and practical
approach to achieving the
desired state of data
quality within an
organization. It is a
'must-read' for any
organization starting out
on the road to data
quality." Susan Stewart
Goubeaux, Director,
Business Intelligence,
FHLBanks Office of
Finance
"Danette has taken what
has previously been
presented in the abstract
and made an excellent,
concrete guide toward
improving data quality."
John Ladley, President of
IMCue Solutions
"This book is a "must-own"
for business and technical
data quality managers and
practitioners. Danette
clearly demonstrates
where her process will add
value to quality projects
that stand-alone or as the
backbone of a successful
data integration effort."
Robert S. Seiner, KIK
Consulting & Educational
Services, LLC, The Data
Administration Newsletter,
LLC
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3. This document may not be
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Information in these documents
is provided "as is" without
warranty of any kind, either
express or implied. The user
assumes the entire risk as to the
use of this document. This
document may not be
distributed for profit.