Data Analytics for Business: Concepts, Methods, Visualization, and AI-Driven Decision Making

Name: Data Analytics for Business: Concepts, Methods, Visualization, and AI-Driven Decision Making
Price: 599 INR
Availability: InStock
ISBN: 978-81-180403-3-0

Dr Chinmaya Kumar Swain; Dr Abhilash Ponnam; Dr Guru Prasad; Mr Tulasi Ram

doi:10.68325/lp.book.013

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Management & Business Analytics / Data Science & AIFeatured

Data Analytics for Business: Concepts, Methods, Visualization, and AI-Driven Decision Making

Authors: Dr Chinmaya Kumar Swain, Dr Abhilash Ponnam, Dr Guru Prasad, Mr Tulasi Ram

Published: October 2026

Paperback ISBN978-81-180403-3-0

Digital ISBN978-81-180403-4-7

Pages389 Pages

Paperback₹599

Digital PDF₹299

RentalFrom ₹59

DOI:https://doi.org/10.68325/lp.book.013

About This Textbook

This book introduces the foundational concepts, practical methods, visualization techniques, and AI-driven frameworks essential for modern business analytics. It connects analytical concepts with business questions, covering descriptive, diagnostic, predictive, and prescriptive analytics alongside industry tools like SQL, Excel, Power BI, Tableau, R, and Python.

Data Analytics for Business: Concepts, Methods, Visualization, and AI-Driven Decision Making is a comprehensive, industry-aligned textbook authored by Dr. Chinmaya Kumar Swain, Dr. Abhilash Ponnam, Dr. Guru Prasad, and Mr. Tulasi Ram. Designed for students and practitioners of management, commerce, and analytics, this book connects core analytical principles with real-world enterprise applications. Progressing across 21 chapters from foundational statistics and exploratory data analysis to machine learning, Big Data architectures (Hadoop, Spark, Data Lakes), and Generative AI, this book includes hands-on labs in SQL, Excel, Power BI, Tableau, R, and Python to empower evidence-based decision making.

Table of Contents (Chapters & Modules)

Chapter 1: Introduction to Data Analytics
Chapter 2: Business Decision Making Using Data
Chapter 3: Data Types and Data Sources
Chapter 4: Data Collection and Data Preparation
Chapter 5: Data Analytics Lifecycle
Chapter 6: Statistics for Business Analytics
Chapter 7: Exploratory Data Analysis (EDA)
Chapter 8: Data Visualization
Chapter 9: Descriptive Analytics
Chapter 10: Diagnostic Analytics
Chapter 11: Predictive Analytics
Chapter 12: Prescriptive Analytics
Chapter 13: SQL for Data Analytics
Chapter 14: Excel for Business Analytics
Chapter 15: Power BI
Chapter 16: Tableau
Chapter 17: R for Data Analytics
Chapter 18: Python for Business Analytics
Chapter 19: Big Data Analytics
Chapter 20: Artificial Intelligence in Data Analytics
Chapter 21: Generative AI For Data Analytics

Academic Subjects:

#Data Analytics for Business#Business Analytics textbook#AI-Driven Decision Making#Data Visualization#SQL for Data Analytics#Power BI Tableau Excel R Python#Dr Chinmaya Kumar Swain#Dr Abhilash Ponnam