Business Analytics: The Science Of Data-Driven Decision Making by U Dinesh Kumar is a comprehensive guide to the field of business analytics, covering all aspects from foundational concepts to advanced techniques. The book consists of 17 chapters designed to provide readers with a thorough understanding of data-driven decision making.

The first chapter introduces the reader to the basics of business analytics, explaining the key components such as descriptive, predictive, and prescriptive analytics through various applications. From there, Chapters 2 to 8 delve into fundamental statistical concepts including descriptive statistics, random variables, confidence intervals, hypothesis testing, analysis of variance, and correlation.

The subsequent chapters focus on specific analytical techniques. Chapters 9 to 13 explore predictive analytics with in-depth discussions on multiple linear regression, logistic regression, decision tree learning, and forecasting methods. Chapter 14 introduces clustering methodologies, while Chapter 15 covers prescriptive analytics by discussing linear programming, integer programming, and goal programming.

The final chapters, 16 and 17, tackle stochastic models and Six Sigma methodologies respectively, providing a complete toolkit for data-driven decision making in various business contexts. With a print length of 714 pages, this book serves as an invaluable resource for students, professionals, and practitioners looking to enhance their skills in business analytics.