Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all factors that affect a business, such as customers, competitors, business partners, economic environment, and internal operations, therefore enabling optimal decisions to be made. This title provides coverage of a broad spectrum of topics currently dispersed throughout data mining and business books. In bringing these topics together for the first time, the book provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence. Starting from a thorough description of decision support systems and data warehousing, the book then moves to a detailed presentation of methods for data mining and inductive learning data. Finally, applications of data mining to relational marketing, models for optimizing the supply chain and analytical methods for performance evaluation are considered. Defining and introducing each concept in turn, it allows those readers with a minimal background in statistics a full understanding of the necessary tools. This is aided by the use of many examples and the inclusion of several case studies.

Business intelligence. Data mining and optimization for decision making.

VERCELLIS, CARLO
2009-01-01

Abstract

Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all factors that affect a business, such as customers, competitors, business partners, economic environment, and internal operations, therefore enabling optimal decisions to be made. This title provides coverage of a broad spectrum of topics currently dispersed throughout data mining and business books. In bringing these topics together for the first time, the book provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence. Starting from a thorough description of decision support systems and data warehousing, the book then moves to a detailed presentation of methods for data mining and inductive learning data. Finally, applications of data mining to relational marketing, models for optimizing the supply chain and analytical methods for performance evaluation are considered. Defining and introducing each concept in turn, it allows those readers with a minimal background in statistics a full understanding of the necessary tools. This is aided by the use of many examples and the inclusion of several case studies.
2009
John Wiley
9780470511381
Machine learning; Data mining; Business intelligence; Optimization
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/505702
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