Books by Our Consultants and Partners
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| Data Analysis with SQL and Excel shows
business managers and data analysts how
to use the relatively simple tools of SQL
and Excel to extract useful business information
from relational databases. Each chapter
explains why and when to perform a particular
type of business analysis to obtain a useful
business result; how to design and perform
the analysis using SQL and Excel; and what
the results look like in SQL and Excel.
The book is full of examples using real
business data. The datasets used in the
book are made available on the companion
web site so readers can execute the many
SQL code examples provided and perform
further exploration on their own.
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The third edition retains the focus of the earlier editions—showing marketing analysts,
business managers, and data mining specialists how to harness data mining
methods and techniques to solve important business problems. The authors
do not assume that readers have a background in statistics or computer science. While never sacrificing accuracy for the sake of simplicity, Linoff and Berry present even complex topics in clear, concise English with minimal use of technical jargon or mathematical formulas. Among the techniques newly covered, or covered in greater depth,
are linear and logistic regression models, incremental response (uplift) modeling, naïve Bayesian models, table lookup models, similarity models, radial basis function networks, expectation maximization (EM) clustering, and swarm intelligence. Entirely new chapters are devoted to data preparation, derived variables, principal components and other variable reduction techniques, and text mining.
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| Non-English
editions available in
French
,
Japanese
, and
Traditional
Chinese
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