🏗️ Data Modeling Fundamentals
Learn the principles of designing effective data models for analytics and business intelligence.
Level:
Intermediate
Tools:
ERD tools
dbt
SQL
Lucidchart
Draw.io
Skills You'll Learn:
Dimensional modeling
Schema design
Normalization
Star schema
Snowflake schema
Step 1: Data Modeling Fundamentals
- 1Understand what data modeling is and why it matters
- 2Learn about different types of data models
- 3Distinguish between OLTP and OLAP systems
- 4Understand the role of data models in analytics
Step 2: Relational Database Concepts
- 1Learn about entities, attributes, and relationships
- 2Understand primary and foreign keys
- 3Practice creating Entity-Relationship Diagrams (ERDs)
- 4Learn about database constraints and integrity
Step 3: Normalization and Denormalization
- 1Understand the first normal form (1NF)
- 2Learn about second normal form (2NF)
- 3Master third normal form (3NF)
- 4Know when to denormalize for performance
Step 4: Dimensional Modeling
- 1Learn the star schema pattern
- 2Understand fact and dimension tables
- 3Practice designing dimension tables
- 4Create fact tables with measures and foreign keys
Step 5: Advanced Dimensional Concepts
- 1Learn about slowly changing dimensions (SCD)
- 2Understand snowflake schema patterns
- 3Work with bridge tables for many-to-many relationships
- 4Design factless fact tables
Step 6: Modern Data Modeling Approaches
- 1Learn about data vault modeling
- 2Understand wide table approaches
- 3Practice with dbt modeling patterns
- 4Design models for self-service analytics
Step 7: Data Model Documentation and Testing
- 1Document your data models effectively
- 2Create data lineage diagrams
- 3Test data model integrity
- 4Validate business rules in your models
Recommended Resources
Ready to Apply Your Knowledge?
Put these fundamental concepts into practice with our hands-on projects and structured roadmaps.