We have great pleasure in presenting First edition “Business Analytics” written for students of UG courses. The related matters are written in a simple and easily understandable.
This volume is an attempt to provide the students with thorough understanding of Business Analytics. We have presented the subject matter in a systematic manner with liberal use of charts and diagrams where ever necessary so as to make it interesting and sustain students’ interest.
Contents –
Module – 1 Introduction to Business Analytics
Introduction
Business Analytics
Descriptive Analytics
Predictive Analytics
Prescriptive Analytics
Business Analytics vs. Business Intelligence
Business Analytics Lifecycle
Role of a Business Analyst
Data Analyst
Data Scientist
Data Warehousing
OLAP
OLTP
Real-World Applications
Banking Applications
E-commerce Applications
Healthcare Applications
Ethics of Data Analytics
Legal Aspects of Data Analytics
Review Questions
Module – 2 Data Mining & Data Preparation
Introduction
Data Mining
Meaning of Data Mining
Evolution of Data Mining
Knowledge Discovery in Databases
CRISP-DM Methodology
Data Mining Techniques
Classification
Clustering
Association
Data Cleaning
Integration
Transformation
Reduction
Challenges of Data Mining
Case studies from Modern Data Mining Applications
Fraud Detection
Churn Prediction
Review Questions
Module – 3 Predictive Modeling Techniques
Introduction
Predictive Modeling Techniques
Supervised Learning
Unsupervised Learning
Linear Regression
Simple Linear Regression
Multiple Linear Regression
Logistic Regression
Time Series
Forecasting Techniques
Decision Trees
Neural Networks
Model Evaluation
Model Deployment
Basics of MLOps
Review Questions
Module – 4 Big Data and Emerging Technologies
Introduction
Big Data
Characteristics of Big Data
3Vs & 5Vs Characteristics
Structured Data
Semi-Structured Data
Unstructured Data
Big Data Tools
Hadoop
Spark
Mobile Data Analytics
Sensor Data Analytics
Social Media Analytics
Sentiment Analysis
Artificial Intelligence
Machine Learning
Deep Learning
Internet of Things
Review Questions
Module – 5 Functional Applications of Business Analytics
Introduction
Financial Analytics
Risk Analytics-Credit Scoring
Marketing Analytics-Customer Segmentation
Campaign Analysis
HR Analytics
Attrition Prediction
Performance Evaluation
Supply Chain Analytics
Demand Forecasting
Route Optimization
Operations Analytics
Process Optimization
Quality Analytics
Retail Analytics
Healthcare Analytics
Review Questions
Module – 6 Practical Lab – Business Analytics Toolkit
Excel for Data Analytics
Pivot Tables
What-if Analysis
Power BI/Tableau: Dashboard Creation
Basic Predictive Modeling using Python/R
Scikit-learn
Stats Models
Exploratory Data Analysis
Group Mini Project
Solving a Real-world Problem using Datasets
