Subject Details
Dept     : MBA
Sem      : 3
Regul    : R2023
Faculty : Viveka T
phone  : 9629843111
E-mail  : viveka.t.mba@snsct.org
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Syllabus

UNIT
1
FOUNDATIONS OF BUSINESS INTELLIGENCE

Introduction to Business Intelligence (BI)- History and Evolution of Business Intelligence - Business Intelligence Architectures - Data Warehousing Basics- Data Warehousing Architecture-ETL Process- Data Integration and the Data Warehouse- Data Quality and Data Governance-OLAP and Multidimensional Data Modeling-Data Mart and its Types-Business Intelligence Tools and Technologies-Trends in Business Intelligence.

UNIT
2
BUSINESS PERFORMANCE MANAGEMENT IN BI

Introduction to Business Performance Management (BPM)-BPM Processes and Methodologies-Strategic Planning and BPM- Performance Measurement Frameworks- Key Performance Indicators (KPIs)- BPM Technologies and Applications-. Enhancing BPM with Data Visualization- Challenges in BPM Implementation- BPM and Continuous Improvement- Aligning BPM with Corporate Strategy - Emerging Trends in BPM

UNIT
3
DATA MINING FOR BUSINESS INTELLIGENCE

Introduction to Data Mining-Data Mining Process-Data Preprocessing for Data Mining- Data Mining Methods- Classification Techniques- Clustering Techniques- Association Rule Mining- Decision Trees and Neural Networks-Text and Web Mining- Data Mining Software Tools- Ethical Issues in Data Mining.

UNIT
4
BUSINESS INTELLIGENCE IMPLEMENTATION AND EMERGING TRENDS

Business Intelligence Implementation Overview- Business Intelligence Initiative Life Cycle-Integration of Business Intelligence Systems-Connecting Business Intelligence Systems to Databases- On-Demand Business Intelligence - Legal, Privacy, and Ethical Issues in Business Intelligence - Web 2.0 and Business Intelligence - Social Networking and Business Intelligence -Virtual Worlds and Business Intelligence -Social Software Integration in Business Intelligence -RFID and Business Intelligence - Reality Mining- Emerging Trends in Business Intelligence .

UNIT
5
TABLEAU FOR BUSINESS INTELLIGENCE

Introduction to Tableau – Bar Chart – Scatter Plots & Clustering – Time Series – Dual Axis Charts – Trend and Forecasting – Leveraging data – Hierarchies & Organizing Data Fields – Dashboard Formatting – Dashboard Design.

Reference Book:

1. Larson, B., & Chang, V. (2016). Enterprise Business Intelligence and Data Warehousing: Program Management Essentials. Morgan Kaufmann. 2. Rausch, P., Sheta, A. F., & Ayesh, A. (2013). Business Intelligence and Performance Management: Theory, Systems and Industrial Applications. Springer. 3.Luhn, H. P. (2019). Business Intelligence: Concepts, Methodologies, Tools, and Applications. IGI Global 4. Marr, B. (2021). Data Strategy: How to Profit from a World of Big Data, Analytics and Artificial Intelligence (2nd ed.). Kogan Page. 5. Berndtsson, M., & Svahnberg, M. (2020). Data Science and Analytics for Ordinary People. Springer.

Text Book:

1.Sharda, R., Delen, D., & Turban, E. (2020). Business Intelligence, Analytics, and Data Science: A Managerial Perspective (5th ed.). Pearson. 2.Turban, E., Sharda, R., & Delen, D. (2011). Business intelligence: A managerial approach (2nd ed.). Pearson