Keith McCormick is the Vice President and General Manager of QueBIT
Consulting's
Advanced Analytics team. He brings a wealth of consulting/training
experience in statistics,
predictive modeling and analytics, and data mining. For many years,
he has worked in the
SPSS community, fi rst as an External Trainer and Consultant for
SPSS Inc., then in a similar
role with IBM, and now in his role with an award winning IBM
partner. He possesses a BS in
Computer Science and Psychology from Worcester Polytechnic
Institute.
He has been using Stats software tools since the early 90s, and has
been training since
1997. He has been doing data mining and using IBM SPSS Modeler
since its arrival in North
America in the late 90s. He is an expert in IBM's SPSS software
suite including IBM SPSS
Statistics, IBM SPSS Modeler (formally Clementine), AMOS, Text
Mining, and Classifi cation
Trees. He is active as a moderator and participant in statistics
groups online including
LinkedIn's Statistics and Analytics Consultants Group. He also
blogs and reviews related
books at KeithMcCormick.com. He enjoys hiking in out of the way
places, fi nding unusual
souvenirs while traveling overseas, exotic foods, and old books.
Dean Abbott is the President of Abbott Analytics, Inc. in San
Diego, California. He has
over two decades experience in applying advanced data mining, data
preparation, and
data visualization methods in real-world data intensive problems,
including fraud detection,
customer acquisition and retention, digital behavior for web
applications and mobile,
customer lifetime value, survey analysis, donation solicitation and
planned giving. He has
developed, coded, and evaluated algorithms for use in commercial
data mining and pattern
recognition products, including polynomial networks, neural
networks, radial basis functions,
and clustering algorithms for multiple software vendors.
He is a seasoned instructor, having taught a wide range of data
mining tutorials and
seminars to thousands of attendees, including PAW, KDD, INFORMS,
DAMA, AAAI, and IEEE
conferences. He is the instructor of well-regarded data mining
courses, explaining concepts
in language readily understood by a wide range of audiences,
including analytics novices,
data analysts, statisticians, and business professionals. He also
has taught both applied
and hands-on data mining courses for major software vendors,
including IBM SPSS Modeler,
Statsoft STATISTICA, Salford System SPM, SAS Enterprise Miner, IBM
PredictiveInsight, Tibco
Spotfi re Miner, KNIME, RapidMiner, and Megaputer Polyanalyst. Meta
S. Brown helps organizations use practical data analysis to solve
everyday business
problems. A hands-on analyst who has tackled projects with up to
$900 million at stake, she
is a recognized expert in cutting-edge business analytics.
She is devoted to educating the business community on effective use
of statistics, data
mining, and text mining. A sought-after analytics speaker, she has
conducted over 4000 hours
of seminars, attracting audiences across North America, Europe, and
South America. Her
articles appear frequently on All Analytics, Smart Data Collective,
and other publications. She
is also co-author of Big Data, Mining and Analytics: Key Components
for Strategic Decisions
(forthcoming from CRC Press, Editor: Stephan Kudyba).
She holds a Master of Science in Nuclear Engineering from the
Massachusetts Institute of
Technology, a Bachelor of Science in Mathematics from Rutgers
University, and professional
certifi cations from the American Society for Quality and National
Association for Healthcare
Quality. She has served on the faculties of Roosevelt University
and National-Louis University. Tom Khabaza is an independent
consultant in predictive analytics and data mining, and
the Founding Chairman of the Society of Data Miners. He is a data
mining veteran of over 20
years and many industries and applications. He has helped to create
the IBM Scott R. Mutchler is the Vice President of Advanced
Analytics Services at QueBIT Consulting LLC. He had spent the first
17 years of his career building enterprise solutions as a DBA,
software developer, and enterprise architect. When Scott discovered
his true passion was for advanced analytics, he moved into advanced
analytics leadership roles where he was able to drive millions of
dollars in incremental revenues and cost savings through the
application of advanced analytics to most challenging business
problems. His strong IT background turned out to be a huge asset in
building integrated advanced analytics solutions. Recently, he was
the Predictive Analytics Worldwide Industrial Sector Lead for IBM.
In this role, he worked with IBM SPSS clients worldwide. He
architected advanced analytic solutions for clients in some of the
world's largest retailers and manufacturers. He received his
Masters from Virginia Tech in Geology. He stays in Colorado and
enjoys an outdoor lifestyle, playing guitar, and travelling.
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