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BITM Business Intelligence

bitmsemester 8

Business Intelligence

Subject Code: IT249

Course Title: Business Intelligence

Course No: IT249

Nature of Course: Theory & Practical

Full Marks: 60

Pass Marks: 30

Credit Hours: 3

Course Description

This course introduces the concepts, techniques, and tools used in business intelligence (BI) and data analytics. Students will learn how BI is used to transform data into insights for decision-making in organizations.

Course Objective

This course aims to enable students to understand the role and importance of Business Intelligence (BI) in modern organizations, learning key concepts and techniques in data warehousing, data mining, and data visualization. They will gain hands-on experience with popular BI tools and technologies while developing the skills needed to analyze and interpret data to support effective decision-making processes.

Course Contents

Course Contents Teaching Methodology Teaching Hours
Unit 1: Introduction to Business Intelligence (5 Hrs.)
Definition and scope of BI Lecture/Lab
Importance of BI in decision-making
Overview of BI tools and technologies
Unit 2: Data Warehousing (8 Hrs.)
Introduction to data warehousing concepts Lecture/Lab
Data warehouse architecture
ETL (Extract, Transform, Load) processes
Data modeling for BI
Unit 3: Data Mining (8 Hrs.)
Introduction to data mining concepts Lecture/Lab
Data preprocessing techniques
Classification and clustering algorithms
Association rule mining
Unit 4: Data Visualization (7 Hrs.)
Principles of data visualization Lecture/Lab
Tools and techniques for data visualization
Dashboard design and best practices
Unit 5: BI Tools and Technologies (12 Hrs.)
Overview of popular BI tools (e.g., Tableau, Power BI) Lecture/Lab
Hands-on experience with BI tools for data analysis and reporting
Introduction to OLAP (Online Analytical Processing)
Unit 6: BI Implementation (8 Hrs.)
Best practices for implementing BI solutions Lecture/Lab
Challenges and considerations in BI implementation
Case studies of successful BI implementations

Text Books

1. Sherman, R. (2014). Business intelligence guidebook: From data integration to analytics. Morgan Kaufmann.
2. Provost, F., & Fawcett, T. (2013). Data science for business: What you need to know about data mining and data-analytic thinking. O'Reilly Media.
3. Kimball, R., & Ross, M. (2013). The data warehouse toolkit: The definitive guide to dimensional modeling. Wiley.

Lab Works

The laboratory work involves learning to use various Business Intelligence (BI) tools and technologies. It also includes implementing data warehousing, data mining, and data visualization techniques.