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Product Description
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.
Business Intelligence provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence.
This book:
- Combines detailed coverage with a practical guide to the mathematical models and analysis methodologies of business intelligence.
- Covers all the hot topics such as data warehousing, data mining and its applications, machine learning, classification, supply optimization models, decision support systems, and analytical methods for performance evaluation.
- Is made accessible to readers through the careful definition and introduction of each concept, followed by the extensive use of examples and numerous real–life case studies.
- Explains how to utilise mathematical models and analysis models to make effective and good quality business decisions.
This book is aimed at postgraduate students following data analysis and data mining courses.
Researchers looking for a systematic and broad coverage of topics in operations research and mathematical models for decision–making will find this an invaluable guide.
From the Back Cover
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.
Business Intelligence provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence.
This book:
- Combines detailed coverage with a practical guide to the mathematical models and analysis methodologies of business intelligence.
- Covers all the hot topics such as data warehousing, data mining and its applications, machine learning, classification, supply optimization models, decision support systems, and analytical methods for performance evaluation.
- Is made accessible to readers through the careful definition and introduction of each concept, followed by the extensive use of examples and numerous real–life case studies.
- Explains how to utilise mathematical models and analysis models to make effective and good quality business decisions.
This book is aimed at postgraduate students following data analysis and data mining courses.
Researchers looking for a systematic and broad coverage of topics in operations research and mathematical models for decision–making will find this an invaluable guide.
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7 of 9 people found the following review helpful
The missing link
9 Feb 2010
Format:Paperback|Amazon Verified Purchase
As a CTO of a company that develops machine learning software(Analytics 1305), I always find it challenging to convince business people about the value of machine learning. Even the scientists in Business intelligence, mainly statisticians, find it hard to understand what machine learning can do. This is because in order to make a connection of their background to machine learning they need to put a lot of effort to read one of the bulky machine learning books. This is not easy since scientists in business intelligence are super busy and they don't have the time to read machine learning theory and translate it to their language.
This book bridges the gap. It speaks the language of machine learning with the "accent" of business intelligence/(industrial and systems engineering). It has helped us tremendously to educate and market our clients about the value of machine learning. It has also helped us (machine learning people) to understand better the business intelligence area. There are a lot of books that talk about analytics/data mining in a very high level. This one talks about the stuff that actually work and have made netflix, amazon, google and yahoo successful companies. I highly recommend this book.
I would also like to note that the editor has done a very good job in the typesetting.
This book bridges the gap. It speaks the language of machine learning with the "accent" of business intelligence/(industrial and systems engineering). It has helped us tremendously to educate and market our clients about the value of machine learning. It has also helped us (machine learning people) to understand better the business intelligence area. There are a lot of books that talk about analytics/data mining in a very high level. This one talks about the stuff that actually work and have made netflix, amazon, google and yahoo successful companies. I highly recommend this book.
I would also like to note that the editor has done a very good job in the typesetting.
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