Course Content

Module 1: Data Modelling Basics

• Data modelling concepts
• Conceptual, logical, physical models
• Entities, attributes, relationships

Module 2: Conceptual & Logical Modelling

• ER modelling
• Normalization
• Keys and relationships

Module 3: Physical Data Modelling

• Logical to physical transformation
• Data types, constraints, indexing

Module 4: Dimensional Modelling

• Facts and dimensions
• Star and snowflake schemas
• Slowly changing dimensions
• Sales Star Schema Design

Module 5: BI & Analytics Modelling

• KPIs and measures
• Aggregations
• Data marts
• BI Reporting Model

Module 6: Data Warehouse Architectures

• Kimball, Inmon, Data Vault
• ELT vs ETL
• Data Warehouse Architecture Design

Module 7: Data Vault Fundamentals

• Data Vault 2.0 concepts
• Hubs, links, satellites
• Historization
• Raw Data Vault Model

Module 8: Data Vault Implementation

• Staging layer
• Hub, link, satellite loading
• Raw Data Vault Implementation

Module 9: Business Vault

• Business Vault concepts
• Derived satellites
• PIT and bridge tables
• Business Vault Design

Module 10: Data Marts from Data Vault

• Dimensional models from Data Vault
• Performance optimization
• Data Vault Data Mart

Module 11: Automation & Governance

• Data Vault automation
• Metadata and data quality
• Automated Data Vault Pipeline

Module 12: Capstone

• End-to-end modelling lifecycle