Prerequisites

• Basic computer literacy
• Fundamental understanding of business concepts
• Basic mathematics and statistics knowledge
• Familiarity with spreadsheet software
• Optional: Basic programming skills
• Computer with minimum 8GB RAM

12-Week Business Intelligence Course Syllabus

Week 1: Introduction to Business Intelligence

• BI definition and core concepts
• Business intelligence value proposition
• Decision-making technologies
• Historical evolution of BI
• Strategic organizational thinking
• Information systems overview
• Technology and business integration

Week 2: Data Warehousing and Architecture

• Data warehouse fundamentals
• Enterprise resource planning
• Data mart concepts
• Architectural design principles
• Data integration strategies
• Enterprise-level data management
• Technological infrastructure

Week 3: Database Management and SQL

• Advanced SQL techniques
• OLTP and OLAP systems
• Database query structures
• Data management principles
• ETL (Extract, Transform, Load) processes
• Database optimization
• Query performance techniques

Week 4: Analytics and Reporting

• Descriptive analytics
• Predictive analytics
• Reporting toolkits
• Dashboard design
• Key performance indicators (KPIs)
• Ad-hoc query development
• Self-service reporting techniques

Week 5: Advanced Analytics Techniques

• On-Line Analytical Processing (OLAP)
• Multidimensional data analysis
• Data mining fundamentals
• Pattern recognition
• Classification methods
• Drill-down and pivot techniques
• Analytical modeling

Week 6: Business Intelligence Tools

• Tableau dashboard creation
• Power BI fundamentals
• Visualization techniques
• Interactive reporting
• Tool selection strategies
• Comparative BI platform analysis
• Practical implementation

Week 7: Decision Support Systems

• Decision-making frameworks
• Strategic intelligence techniques
• Automated decision systems
• Organizational decision modeling
• Risk assessment strategies
• Computational decision support
• Technological decision frameworks

Week 8: Customer Relationship Management

• CRM integration with BI
• Customer data analysis
• Relationship intelligence
• Customer segmentation
• Behavioral analytics
• Personalization strategies
• Customer insights generation

Week 9: Big Data and Advanced Technologies

• Big data fundamentals
• Cloud computing integration
• Distributed computing concepts
• Scalable data solutions
• Advanced analytics platforms
• Machine learning integration
• Emerging technological trends

Week 10: Data Visualization and Communication

• Advanced visualization techniques
• Data storytelling
• Interactive dashboard design
• Presentation of analytical insights
• Communication strategies
• Visual analytics best practices
• Compelling narrative development

Week 11: Business Intelligence Ethics

• Ethical data usage
• Privacy considerations
• Algorithmic bias detection
• Responsible AI development
• Compliance frameworks
• Ethical decision-making
• Regulatory landscape understanding

Week 12: Capstone Project and Career Preparation

• End-to-end BI project
• Portfolio development
• Industry best practices
• Implementation strategies
• Professional networking
• Career guidance
• Final project presentations

Learning Outcomes

• Comprehensive BI technology understanding
• Advanced analytics skill development
• Strategic decision-making capabilities
• Professional BI tool proficiency
• Ethical data management expertise
• Practical implementation knowledge
• Industry-ready business intelligence skills

Certification

Students receive a comprehensive Business Intelligence certification upon successful course completion.

Note: Course content may be dynamically updated to reflect emerging industry trends and technological advancements.