Titled ‘Business Analytics – The Science of Data-Driven Decision Making’, the book provides a holistic perspective of analytics with theoretical foundations and applications of the theory using examples across several industries
04 September, 2017, Bengaluru: A book titled, ‘Business Analytics – The Science of Data-Driven Decision Making’, authored by Professor U Dinesh Kumar, faculty and Chairperson, Decision Sciences and Information Systems area, IIM Bangalore, has been published by Wiley India Pvt. Ltd.
Written with the aim of becoming the primary resource for students of Business Analytics, this book provides a holistic perspective of analytics with theoretical foundations and applications of the theory using examples across several industries. The content of the book starts with the foundations of data science and addresses all components of analytics, such as, descriptive, predictive and prescriptive analytics topics which are discussed using examples from several industries, as well as nine analytics case studies distributed by Harvard Business Publishing and used by several institutes across the world. The book is enriched with 10 years of teaching experience of the author at various programmes in IIM Bangalore and several training and consulting projects carried out by him.
About the book: The key features of the book are: it provides equal importance to theory and practice with examples across industries; the case studies provide a deeper understanding of analytics techniques and deployment of analytics-driven solutions; it has thorough coverage of topics such as basic probability concepts, probability distributions, hypothesis testing, multiple linear regression, logistic regression, decision trees, forecasting, clustering, prescriptive analytics, stochastic models and Six Sigma; offers real data sets for students to practice various analytics techniques; it consists of discussion of analytics applications in industries such as banking and finance, eCommerce, healthcare, manufacturing, retail and services; has multiple-choice questions at the end of the chapter which will ensure that the reader has understood the learning outcomes; the microsite of the book lists the datasets used in the book, and the case studies in this book are distributed through the Harvard Business Publishing (HBP) case portal.
The book has 17 chapters and the first few chapters are dedicated to foundations of Business Analytics. Introduction to Business Analytics and its components such as descriptive, predictive, and prescriptive analytics along with several applications are discussed in Chapter 1. In Chapters 2 to 8, basic statistical concepts are discussed, such as descriptive statistics, concept of random variables, discrete and continuous random variables, confidence interval, hypothesis testing, analysis of variance and correlation. Chapters 9 to 13 are dedicated to predictive analytics techniques such as multiple linear regression, logistic regression, decision tree learning, and forecasting techniques. Clustering is discussed in Chapter 14. Chapter 15 is about prescriptive analytics in which concepts such as linear programming, integer programming, and goal programming are discussed. Stochastic models and Six Sigma are discussed in Chapters 16 and 17, respectively. Each chapter is enriched with several solved problems, multiple-choice questions, and exercise problems. Many chapters include case studies that will improve understanding of the concepts and enable students to understand how analytics is used by the industry.
About the author: Prof. Dinesh Kumar is also the Chairperson, Data Centre and Analytics Lab, an initiative of IIMB set up to support interdisciplinary empirical research using data on primarily Indian as well as other emerging markets, and Chairperson of IIMB’s Executive Post Graduate Programme in Management (EPGP). He holds a PhD in Mathematics from IIT Bombay. He introduced the Business Analytics elective course in 2008 to the Post Graduate Programme in Management (PGP) students at IIM Bangalore and started one of the first certificate programmes in Business Analytics in India in 2010.
Prof. Dinesh Kumar has over 20 years of teaching and research experience. He has published more than 60 research articles in leading academic journals. Twenty-eight of his case studies on Business Analytics, based on Indian and multinational organizations, have been published at the Harvard Business Publishing’s case portal. He has also carried out predictive and prescriptive analytics consulting projects for leading organizations. Moreover, he conducts corporate training programmes on Analytics for several companies.
Prof. Dinesh Kumar is the Founding President of the Analytics Society of India (ASI). He was awarded the Best Young Teacher Award by the Association of Indian Management Institutions in 2003. He is listed as one of the top 10 Analytics academics in India by the Analytics India magazine.
Titled ‘Business Analytics – The Science of Data-Driven Decision Making’, the book provides a holistic perspective of analytics with theoretical foundations and applications of the theory using examples across several industries
04 September, 2017, Bengaluru: A book titled, ‘Business Analytics – The Science of Data-Driven Decision Making’, authored by Professor U Dinesh Kumar, faculty and Chairperson, Decision Sciences and Information Systems area, IIM Bangalore, has been published by Wiley India Pvt. Ltd.
Written with the aim of becoming the primary resource for students of Business Analytics, this book provides a holistic perspective of analytics with theoretical foundations and applications of the theory using examples across several industries. The content of the book starts with the foundations of data science and addresses all components of analytics, such as, descriptive, predictive and prescriptive analytics topics which are discussed using examples from several industries, as well as nine analytics case studies distributed by Harvard Business Publishing and used by several institutes across the world. The book is enriched with 10 years of teaching experience of the author at various programmes in IIM Bangalore and several training and consulting projects carried out by him.
About the book: The key features of the book are: it provides equal importance to theory and practice with examples across industries; the case studies provide a deeper understanding of analytics techniques and deployment of analytics-driven solutions; it has thorough coverage of topics such as basic probability concepts, probability distributions, hypothesis testing, multiple linear regression, logistic regression, decision trees, forecasting, clustering, prescriptive analytics, stochastic models and Six Sigma; offers real data sets for students to practice various analytics techniques; it consists of discussion of analytics applications in industries such as banking and finance, eCommerce, healthcare, manufacturing, retail and services; has multiple-choice questions at the end of the chapter which will ensure that the reader has understood the learning outcomes; the microsite of the book lists the datasets used in the book, and the case studies in this book are distributed through the Harvard Business Publishing (HBP) case portal.
The book has 17 chapters and the first few chapters are dedicated to foundations of Business Analytics. Introduction to Business Analytics and its components such as descriptive, predictive, and prescriptive analytics along with several applications are discussed in Chapter 1. In Chapters 2 to 8, basic statistical concepts are discussed, such as descriptive statistics, concept of random variables, discrete and continuous random variables, confidence interval, hypothesis testing, analysis of variance and correlation. Chapters 9 to 13 are dedicated to predictive analytics techniques such as multiple linear regression, logistic regression, decision tree learning, and forecasting techniques. Clustering is discussed in Chapter 14. Chapter 15 is about prescriptive analytics in which concepts such as linear programming, integer programming, and goal programming are discussed. Stochastic models and Six Sigma are discussed in Chapters 16 and 17, respectively. Each chapter is enriched with several solved problems, multiple-choice questions, and exercise problems. Many chapters include case studies that will improve understanding of the concepts and enable students to understand how analytics is used by the industry.
About the author: Prof. Dinesh Kumar is also the Chairperson, Data Centre and Analytics Lab, an initiative of IIMB set up to support interdisciplinary empirical research using data on primarily Indian as well as other emerging markets, and Chairperson of IIMB’s Executive Post Graduate Programme in Management (EPGP). He holds a PhD in Mathematics from IIT Bombay. He introduced the Business Analytics elective course in 2008 to the Post Graduate Programme in Management (PGP) students at IIM Bangalore and started one of the first certificate programmes in Business Analytics in India in 2010.
Prof. Dinesh Kumar has over 20 years of teaching and research experience. He has published more than 60 research articles in leading academic journals. Twenty-eight of his case studies on Business Analytics, based on Indian and multinational organizations, have been published at the Harvard Business Publishing’s case portal. He has also carried out predictive and prescriptive analytics consulting projects for leading organizations. Moreover, he conducts corporate training programmes on Analytics for several companies.
Prof. Dinesh Kumar is the Founding President of the Analytics Society of India (ASI). He was awarded the Best Young Teacher Award by the Association of Indian Management Institutions in 2003. He is listed as one of the top 10 Analytics academics in India by the Analytics India magazine.