Business Analytics Principles, Concepts, And Applications With Sas: What, Why, And How

Hardcover | October 7, 2014

byMarc J. Schniederjans, Dara G. Schniederjans, Christopher M. Starkey

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Learn everything you need to know to start using business analytics and integrating it throughout your organization.

Business Analytics Principles, Concepts, and Applications with SAS brings together a complete, integrated package of knowledge for newcomers to the subject. The authors present an up-to-date view of what business analytics is, why it is so valuable, and most importantly, how it is used. They combine essential conceptual content with clear explanations of the tools, techniques, and methodologies actually used to implement modern business analytics initiatives.

 

They offer a proven step-wise approach to designing an analytics program, and successfully integrating it into your organization, so it effectively provides intelligence for competitive advantage in decision making.

Using step-by-step examples, the authors identify common challenges that can be addressed by business analytics, illustrate each type of analytics (descriptive, prescriptive, and predictive), and guide users in undertaking their own projects. Illustrating the real-world use of statistical, information systems, and management science methodologies, these examples help readers successfully apply the methods they are learning.

 

Unlike most competitive guides, this text demonstrates the use of SAS software, permitting instructors to spend less time teaching software and more time focusing on business analytics itself.

 

Business Analytics Principles, Concepts, and Applications with SAS will be a valuable resource for all beginning-to-intermediate level business analysts and business analytics managers; for MBA/Masters' degree students in the field; and for advanced undergraduates majoring in statistics, applied mathematics, or engineering/operations research.

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From the Publisher

Learn everything you need to know to start using business analytics and integrating it throughout your organization. Business Analytics Principles, Concepts, and Applications with SAS brings together a complete, integrated package of knowledge for newcomers to the subject. The authors present an up-to-date view of what business ...

From the Jacket

Today’s Most Complete, Up-to-Date, and Practical Introduction to Business Analytics with SAS Covers both core concepts and modern SAS-based techniques Presents strategies and best practices for descriptive, predictive, and prescriptive analytics For all beginning-to-intermediate-level analysts and analytics managers and for MBA/Maste...

Marc J. Schniederjans is the C. Wheaton Battey Distinguished Professor of Business in the College of Business Administration at the University of Nebraska-Lincoln and has served on the faculty of three other universities. Professor Schniederjans is a Fellow of the Decision Sciences Institute (DSI) and in 2014-2015 will serve as DSI’s p...

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Format:HardcoverDimensions:352 pages, 9.2 × 7.1 × 1.2 inPublished:October 7, 2014Publisher:Pearson EducationLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0133989402

ISBN - 13:9780133989403

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Table of Contents

Preface      xvi
PART I: What Is Business Analytics?       1
Chapter 1: What Is Business Analytics?       3
PART II: Why Is Business Analytics Important?       15
Chapter 2: Why Is Business Analytics Important?       17
Chapter 3: What Resource Considerations Are Important to Support Business Analytics?       29
PART III: How Can Business Analytics Be Applied?       43
Chapter 4: How Do We Align Resources to Support Business Analytics within an Organization?       45
Chapter 5: What Is Descriptive Analytics?       63
Chapter 6: What Is Predictive Analytics?       95
Chapter 7: What Is Prescriptive Analytics?       117
Chapter 8: A Final Business Analytics Case Problem      137
PART IV: Appendixes      161
Appendix A: Statistical Tools      163
Appendix B: Linear Programming      195
Appendix C: Duality and Sensitivity Analysis in Linear Programming      229
Appendix D: Integer Programming      249
Appendix E: Forecasting      257
Appendix F: Simulation      281
Appendix G: Decision Theory      289
Index      321