Skip to content
Beta

Data Modeling and Warehousing

In 1 trail

Last updated on

Course Overview

Section titled “Course Overview”

Data modeling is what separates good data engineers from great ones: this course teaches the art and science of designing data structures optimized for analytics and reporting, transforming normalized transactional data into dimensional models that enable fast business intelligence. It covers both the “how” and the “why” behind dimensional modeling — when to denormalize for performance and how to handle scenarios like slowly changing dimensions.

Across four modules it moves from dimensional modeling foundations (facts, dimensions, star schemas) to building fact and dimension tables, handling slowly changing dimensions with the standard SCD strategies, and warehouse architecture patterns (Kimball vs. Inmon) with performance optimization.

What You’ll Learn

Section titled “What You’ll Learn”
  • Design and implement star and snowflake schemas for data warehouses
  • Create effective fact and dimension tables that support business analytics
  • Handle slowly changing dimensions (SCDs) using appropriate strategies
  • Understand the transition from normalized to denormalized models
  • Build data warehouse architectures that scale
  • Optimize query performance in analytical environments

Modules

Section titled “Modules”
  • Foundations of Dimensional Modeling
  • Building Fact and Dimension Tables
  • Slowly Changing Dimensions
  • Data Warehouse Architecture and Optimization
STACKIT documentation university.stackit.cloud View Course on STACKIT University Open the documentation
Asset historyActive 2 of the last 12 weeksTMUpdatedNo updates · 1 bar = 1 week i
Maintainers
TMTobias M.Head of STACKIT Cloud Framework · STACKITOwnerActive 12 of the last 12 weeks · 168 updatesSTACKITwww.linkedin.com/in/tobias-müller-011304172CC.C1SCF Core · STACKITOwnerActive 5 of the last 12 weeks · 23 updatesSTACKITwww.linkedin.com/in/can-celik-645932315can.celik1@digits.schwarzContributed in STACKIT