Business Intelligence & Analytics

Unit I

Introduction to Business Intelligence and Analytics: Introduction to Business Intelligence and Analytics, Data Warehousing and Data Mining, Data Extraction, Transformation, and Loading (ETL), Introduction to Analytics: Descriptive, Predictive, and Prescriptive Analytics.

Unit II

Data Analysis and Visualization: Exploratory Data Analysis (EDA), Statistical Analysis for Business Intelligence, Data Visualization Techniques and Tools, Interactive Dashboards and Reports

Unit III

Machine Learning for Business Analytics: Supervised and Unsupervised Learning Algorithms, Regression and Classification Models, Clustering Techniques for Customer Segmentation, Recommendation Systems

Unit IV

Big Data Analytics and Emerging Trends: Introduction to Big Data Analytics, Hadoop and Map Reduce, Real-time Analytics and Streaming Data, Emerging Trends in Business Intelligence and Analytics

Textbooks:

1. "Business Intelligence: A Managerial Perspective on Analytics" by Ramesh Sharda, Dursun Delen, Efraim Turban
2. "Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking" by Foster Provost, Tom Fawcett
3. "Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython" by Wes McKinney

Reference Books:

1. "The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling" by Ralph Kimball, Margy Ross
2. "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die" by Eric Siegel
3. "Big Data Analytics: Methods and Applications" by Chang Liu, Quan Z. Sheng, Jian Yu, Yongrui Qin