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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.

• Sales Rank: #2289068 in eBooks
• Published on: 2011-08-15
• Released on: 2011-08-15
• Format: Kindle eBook

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.

About the Author
Carlo Vercellis - School of Management, Politecnico di Milano, Italy

As well as teaching courses in Operations Research and Business Intelligence, Professor Vercellis is director of the research group MOLD (Mathematical Modeling, Optimization, Learning from Data). He has written four book in Italian, contributed to numerous other books, and has had many papers published in a variety of international journals.

Most helpful customer reviews

11 of 13 people found the following review helpful.
The missing link
By Analytics
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.

0 of 0 people found the following review helpful.
Fast Delivery
By MalMurph
I got this for personal reading. It is very comprehensive and great for any type of skill level! I highly recommend

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• Published on: 1609
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[C175.Ebook] Free Ebook Introduction to Static Analysis Using SolidWorks Simulation, by Radostina V. Petrova

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Uses Finite Element Analysis (FEA) as Implemented in SolidWorks Simulation

Outlining a path that readers can follow to ensure a static analysis that is both accurate and sound, Introduction to Static Analysis using SolidWorks Simulation effectively applies one of the most widely used software packages for engineering design to the concepts of static analysis. This text utilizes a step-by-step approach to introduce the use of a finite element simulation within a computer-aided design (CAD) tool environment. It does not center on formulae and the theory of FEM; in fact, it contains essentially no theory on FEM other than practical guidelines. The book is self-contained and enables the reader to progress independently without an instructor. It is a valuable guide for students, educators, and practicing professionals who wish to forego commercial training programs, but need to refresh or improve their knowledge of the subject.

Classroom Tested with Figures, Examples, and Homework Problems

The book contains more than 300 illustrations and extensive explanatory notes covering the features of the SolidWorks (SW) Simulation software. The author presents commonly used examples and techniques highlighting the close interaction between CAD modelling and FE analysis. She describes the stages and program demands used during static analysis, details different cases, and explores the impact of selected options on the final result. In addition, the book includes hands-on exercises, program commands, and a summary after each chapter.

• Explores the static studies of simple bodies to more complex structures
• Considers different types of loads and how to start the loads property managers
• Studies the workflow of the run analysis and discusses how to assess the feedback provided by the study manager
• Covers the generation of graphs
• Determines how to assess the quality of the created mesh based on the final results and how to improve the accuracy of the results by changing the mesh properties
• Examines a machine unit with planar symmetrical geometry or with circular geometry exposed to symmetrical boundary conditions
• Compares 3D FEA to 2D FEA
• Discusses the impact of the adopted calculating formulation by comparing thin-plate results to thick-plate results

Introduction to Static Analysis using SolidWorks Simulation equips students, educators, and practicing professionals with an in-depth understanding of the features of SW Simulation applicable to static analysis (FEA/FEM).

• Sales Rank: #928920 in Books
• Published on: 2014-09-09
• Original language: English
• Number of items: 1
• Dimensions: 10.00" h x .90" w x 7.10" l, .0 pounds
• Binding: Hardcover
• 353 pages

Review

"The contents seem to be quite logical and appropriate for this book: After explaining the theory, special examples with increasing complexity are worked out in detail."
―Alois Steindl, Vienna University of Technology, Austria

About the Author

Radostina Petrova was awarded a PhD degree in applied mechanics by the Technical University of Sofia, Bulgaria. Since 2007, she has been an associate professor in dynamics, strength and reliability of machines, devices and systems at the Technical University of Sofia. Her research interests and fields of expertise include multi-body dynamic simulation of mechanical systems; nonlinear structural analysis; structural modelling and analysis using FEM; simulation-based, design optimization of mechanical systems; CAD/CAE (FEA) design of structures and mechanical systems, particularly dynamic analysis and simulations; structural engineering; wind engineering; fluid–structure interaction; exposure of slender structures (aerial ropeways, wind turbines, etc.) to random dynamic excitation; and interaction and combination of different software platforms/data for solving different structural problems.

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