Introduction
Begins with a historical overview and the architectural framework of business analytics
Definitions, distinctions between analysis and analytics, and types (descriptive, predictive, prescriptive) are discussed
Applications across finance, marketing, human resources, and healthcare are explored alongside a case study and summary, followed by exercises and multiple-choice questions
Data Preparation
Focuses on the data preparation process, using MS-Excel for cleaning and validation, identifying outliers, and understanding covariance and correlation matrix
Practical application to business, summary, exercises, and multiple-choice questions are included
Data Summarisation and Visualisation
Covers types of data summarisation and visualisation, with an emphasis on using Tableau
The chapter concludes with exercises and multiple-choice questions
Getting Started with R
Introduces R and R Studio, highlighting the advantages of R, installation processes, data structures in R, and their application to business
Summarised with exercises and multiple-choice questions
Descriptive Statistics Using R
Measures of central tendency, dispersion, and relationship between variables are explored
Focuses on data visualisation using R through various plots and business applications, followed by a summary, exercises, and questions
Predictive Analytics
Discusses simple and multiple linear regression models, confidence and prediction intervals, regression analysis using R, and their applications in business
A summary, exercises, and multiple-choice questions are provided
Textual Analysis
Highlights the significance, applications, and challenges of textual data analysis
Introduces methods and techniques like word clouds, tree maps, and sentiment analysis using R, with a focus on business applications, summarised with exercises and questions
Ethics in Business Analytics
Addresses the meaning and importance of ethics in analytics, ethical issues, and considerations for ethical conduct
Concludes with practical applications to business, a summary, exercises, and multiple-choice questions

This book underscores the pivotal role of data in the contemporary business landscape, blending theoretical knowledge with practical application to prepare students and professionals for data analysis and strategic implementation. It aligns with the UGCF 2022 syllabus under the National Education Policy of the University of Delhi. Covering a wide array of topics from data preparation to ethics in business analytics, it integrates tools like MS Excel, Tableau, and R for comprehensive learning in business analytics

English