Learn everything you need to know to start using business analytics and integrating it throughout your organization.Business Analytics Principles, Concepts, and Applications 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 IBM's menu-based SPSS software, permitting instructors to spend less time teaching software and more time focusing on business analytics itself.
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.
Table of contents
- About This eBook
- Title Page
- Copyright Page
- Dedication Page
- Table of Contents
- About the Authors
- Part I: What Are Business Analytics
Part II: Why Are Business Analytics Important
- 2. Why Are Business Analytics Important?
- 3. What Resource Considerations Are Important to Support Business Analytics?
Part III: How Can Business Analytics Be Applied
- 4. How Do We Align Resources to Support Business Analytics within an Organization?
- 5. What Are Descriptive Analytics?
- 6. What Are Predictive Analytics?
- 7. What Are Prescriptive Analytics?
- 8. A Final Business Analytics Case Problem
Part IV: Appendixes
- A. Statistical Tools
B. Linear Programming
- B.1. Introduction
- B.2. Types of Linear Programming Problems/Models
- B.3. Linear Programming Problem/Model Elements
- B.4. Linear Programming Problem/Model Formulation Procedure
- B.5. Computer-Based Solutions for Linear Programming Using the Simplex Method
- B.6. Linear Programming Complications
- B.7. Necessary Assumptions for Linear Programming Models
- B.8. Linear Programming Practice Problems
- C. Duality and Sensitivity Analysis in Linear Programming
- D. Integer Programming
- E. Forecasting
- F. Simulation
G. Decision Theory
- G.1. Introduction
- G.2. Decision Theory Model Elements
- G.3. Types of Decision Environments
- G.4. Decision Theory Formulation
- G.5. Decision-Making Under Certainty
- G.6. Decision-Making Under Risk
- G.7. Decision-Making under Uncertainty
- G.8. Expected Value of Perfect Information
- G.9. Sequential Decisions and Decision Trees
- G.10. The Value of Imperfect Information: Bayes’s Theorem
- G.11. Decision Theory Practice Problems
- Title: Business Analytics Principles, Concepts, and Applications: What, Why, and How
- Release date: April 2014
- Publisher(s): Pearson
- ISBN: 9780133552256
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