Synopses & Reviews
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/Masters or advanced undergraduate students
This guide brings together all the business analytics knowledge and SAS techniques you need to gain valuable intelligence for competitive advantage in decision making.
Starting with the basics, the authors offer 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, step-by-step explanations of how to perform each important statistical task with SAS.
Using SAS-based examples, they identify common challenges that can be addressed by business analytics, illustrate each type of analytics (descriptive, prescriptive, and predictive), and offer indispensable practical guidance for undertaking your own projects.
Business analytics can help you sort through massive amounts of data, identify meaningful patterns, transform patterns into insights, and use those insights to make more profitable decisions. The authors start with a complete conceptual introduction, explaining how business analytics can drive competitive advantage and how to align your organization to make the most of it. You’ll find realistic coverage of key managerial and technical issues, from organizational structure to data quality.
Next, you’ll master practical methodologies, strategies, and best practices for performing each leading form of analytics with SAS: descriptive, predictive, and prescriptive. Throughout, you’ll learn from realistic case studies and solved problems and get hands-on experience with powerful SAS software tools. A capstone SAS-based project integrates key processes and techniques, preparing you to succeed on your own.
- What is business analytics?
- What questions can it answer?
- How can it drive competitive advantage?
- What resources and skills do you need?
- How do you prepare the organization for it?
- What obstacles must you overcome?
- What are the key statistical techniques?
- How do you perform each analytic task with SAS?
- How do you handle entire projects in SAS, from start to finish?
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.
About the Author
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 president. His prior experience includes owning and operating his own truck leasing business. He is currently a member of the Institute of Supply Management (ISM), the Production and Operations Management Society (POMS), and Decision Sciences Institute (DSI). Professor Schniederjans has taught extensively in operations management and management science. He has won numerous teaching awards and is an honorary member of the Golden Key honor society and the Alpha Kappa Psi business honor society. He has published more than a hundred journal articles and has authored or coauthored twenty books in the field of management. The title of his most recent book is Reinventing the Supply Chain Life Cycle
, and his research has encompassed a wide range of operations management and decision science topics. He has also presented more than one hundred research papers at academic meetings. Professor Schniederjans is serving on five journal editorial review boards, including Computers & Operations Research
, International Journal of Information & Decision Sciences
, International Journal of Information Systems in the Service Sector
, Journal of Operations Management
, and Production and Operations Management
. He is also serving as an area editor for the journal Operations Management Research
and as an associate editor for the International Journal of Strategic Decision Sciences
and International Journal of the Society Systems Science and Management Review : An International Journal
(Korea). In addition, Professor Schniederjans has served as a consultant and trainer to various business and government agencies.
Dara G. Schniederjans is an assistant professor of Supply Chain Management at the University of Rhode Island, College of Business Administration. She has published articles in journals such as Decision Support Systems, Journal of the Operational Research Society, and Business Process Management Journal. She has also coauthored two text books and coedited a readings book. She has contributed chapters to readings utilizing quantitative and statistical methods. Dara has served as a guest coeditor for a special issue on Business Ethics in Social Sciences in the International Journal of Society Systems Science. She has also served as a website coordinator for Decisions Sciences Institute. She currently teaches courses in Supplier Relationship Management and Operations Management.
Christopher M. Starkey is an economics student at the University of Connecticut-Storrs. He has presented papers at the Academy of Management and Production and Operations Management Society meetings. He currently teaches courses in Principles of Microeconomics and has taught Principles of Macroeconomics. His current research interests include macroeconomic and monetary policy, as well as other decision-making methodologies.
Table of Contents
Part 1. Introduction to Business Analytics
1. What is Business Analytics?
2. Why is Business Analytics Important?
Part 2. Integrating Business Analytics into the Organization
3. What Resource Considerations are Important to Support Business Analytics?
4. How Do We Align Resources to Support Business Analytics within an Organization?
Part 3. Descriptive Analytics
5. What is Descriptive Analytics?
6. How Do We Use Descriptive Analytics?
Part 4. Predictive Analytics
7. What is Predictive Analytics?
8. How Do We Use Predictive Analytics?
Part 5. Prescriptive Analytics
9. What is Prescriptive Analytics?
10. How Do We Use Prescriptive Analytics?
The first text to bring together all the knowledge you need to start implementing business analytics: core concepts, methods, tools, and more.