Data Modeling and Warehouse Design

About this course

Design dimensional models with star and snowflake schemas for analytical workloads. Implement slowly changing dimensions, surrogate keys, and compare OLTP versus OLAP storage patterns.

• 20 lessons
• 2 h
• intermediate

What you'll learn

• Define data modeling and its importance in analytical environments
• Differentiate conceptual, logical, and physical data models and their use cases
• Identify the key stakeholders and goals of analytical data modeling
• Contrast OLTP and OLAP workloads based on query patterns, data volume, and concurrency
• Explain how storage and indexing strategies differ between OLTP and OLAP
• Recognize the implications for schema design in each environment

Finishing the course

• 80 knowledge-check questions along the way, so you know the ideas stuck before you move on.
• Watching is free and needs no account. Sign in to save your progress. Pass each lesson's quiz (60%+) to earn the certificate. Each certificate has its own public verification link to share, marked quiz-verified.

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