This conceptual 3-day course dives into the foundations of BI and data modeling, emphasizing theory and best practices. You’ll explore data architecture design, relational and dimensional modeling, ETL strategies, and governance frameworks. Through case studies and collaborative exercises, you’ll learn to align data models with business goals and ensure scalability. Perfect for analysts, architects, and decision-makers.

BI & Data Architecture Foundations

• Core BI concepts: Data warehouses, lakes, and marts.
• Business requirements gathering: Aligning data models with stakeholder needs.
• Data profiling: Assessing quality, completeness, and consistency.
• Introduction to relational vs. dimensional modeling.

Data Modeling Techniques

• Relational modeling: Entities, attributes, and normalization (1NF, 2NF, 3NF).
• Dimensional modeling: Star and snowflake schemas.
• Semantic modeling: Designing business-friendly logical layers.
• ETL/ELT strategies: Batch vs. real-time data pipelines.

Governance & Scaling BI Solutions

• Data governance: Metadata management, lineage, and quality frameworks.
• Security: Role-based access control (RBAC) and anonymization.
• Optimizing models for performance and scalability.
• Collaboration: Versioning, documentation, and change management.

Upon completion of this course, learners will be able to: 

• Design relational and dimensional models aligned with business objectives.
• Develop ETL strategies for efficient data integration.
• Apply governance frameworks to ensure data quality and security.
• Collaborate with stakeholders to translate requirements into scalable architectures.

• Case studies: Retail inventory optimization, financial reporting.
• Conceptual workshops: Whiteboard modeling sessions.
• Group discussions: Balancing business needs vs. technical constraints.
• Guided templates: Data modeling canvas, governance checklists.