Course overview

A Data Warehouse is a foundation and core component of any data analytics, business intelligence solution. Its building and design significantly differ from the classic transactional OLTP database and requires a specific set of skills. So the goal of this course is first to give a birds-eye view on the different Data warehouse architectures and high-level approaches and then go into the depth of how to design and model the target storage according to the industry best practices as well as how to bring the data from the disparate source into it in a most efficient and reliable way.

Course topics

  • Data Warehouse Design Big Picture:
    • Data Warehouse Architectures:
      • Inmon’s Corporate Information Factory
      • Kimball’s Chess Pieces
      • Data Vault
    • Emerging Tools and Technologies Review
      • OLAP Engines and Column Store engines/indexes
      • MPP Analytics Systems and DW Appliances
      • Cloud Managed services
  • The Data Warehouse Lifecycle
  • Multi-Dimensional Modelling
    • Basics
    • Advanced Patterns
    • EDW Bus Matrix
  • ETL Design
    • ETL Architecture
    • Data Flow:
      • Extracting
      • Cleaning and Conforming
      • Delivering Dimension Tables
      • Delivering Fact Tables
    • Streaming vs Batch Data Processing


Relational Database Design, understanding the basic concepts of normalization and de-normalization, ER diagrams, and its building blocks entities, attributes, relationships.

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