Overview
- Offers a comprehensive introductory approach to business analytics that includes an emphasis on big data handling, applications in different verticals and case studies
- Highlights big data handling, applications of analytics in different verticals, and real life case studies
- Includes exercises for each chapter and downloadable use cases for students and professionals to practice and test the analytics tools
- Request lecturer material: sn.pub/lecturer-material
Part of the book series: International Series in Operations Research & Management Science (ISOR, volume 264)
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Table of contents (30 chapters)
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Front Matter
Keywords
About this book
This comprehensive edited volume is the first of its kind, designed to serve as a textbook for long-duration business analytics programs. It can also be used as a guide to the field by practitioners. The book has contributions from experts in top universities and industry. The editors have taken extreme care to ensure continuity across the chapters.
The material is organized into three parts: A) Tools, B) Models and C) Applications. In Part A, the tools used by business analysts are described in detail. In Part B, these tools are applied to construct models used to solve business problems. Part C contains detailed applications in various functional areas of business and several case studies. Supporting material can be found in the appendices that develop the pre-requisites for the main text.
Every chapter has a business orientation. Typically, each chapter begins with the description of business problems that are transformed into data questions; and methodology is developed to solve these questions. Data analysis is conducted using widely used software, the output and results are clearly explained at each stage of development. These are finally transformed into a business solution. The companion website provides examples, data sets and sample code for each chapter.
Editors and Affiliations
About the editors
Bhimasankaram Pochiraju obtained his Ph.D. in Statistics from the Indian Statistical Institute. He was the Clinical Professor of Statistics, Executive Director of Applied Statistics and Computing Lab and Faculty Director, Certificate Programme in Business Analytics at the Indian School of Business. He was formerly Professor of Statistics and Head, SQC & OR Division at the Indian Statistical Institute. He co-authored a text book and a research monograph in Linear Algebra. His areas of research interest include Analytics, Causal Inference and Linear Algebra.
Sridhar Seshadri obtained his PhD at the University of California, Berkeley after graduating from the Indian Institute of Technology, Madras, India and the Indian Institute of Management, Ahmedabad, India. He is currently Professor and Area Leader of IS, Operations Management and Supply Chain Management areas at the Geis College of Business. He has also been a faculty member at The Indian School of Business, The University of Texas at Austin, New York University and the Administrative Staff College of India. During his teaching career, he was awarded the Stern School of Business Teaching Excellence Award (1998) and recognized as the Stern School of Business Undergraduate Teacher of the Year in 1997. His current research includes Analytics, Pricing and Revenue Optimization and Risk Management in supply chains.
Bibliographic Information
Book Title: Essentials of Business Analytics
Book Subtitle: An Introduction to the Methodology and its Applications
Editors: Bhimasankaram Pochiraju, Sridhar Seshadri
Series Title: International Series in Operations Research & Management Science
DOI: https://doi.org/10.1007/978-3-319-68837-4
Publisher: Springer Cham
eBook Packages: Business and Management, Business and Management (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-319-68836-7Published: 30 July 2019
eBook ISBN: 978-3-319-68837-4Published: 10 July 2019
Series ISSN: 0884-8289
Series E-ISSN: 2214-7934
Edition Number: 1
Number of Pages: XVI, 980
Number of Illustrations: 87 b/w illustrations, 191 illustrations in colour
Topics: Operations Research/Decision Theory, Statistics for Business, Management, Economics, Finance, Insurance, Big Data/Analytics