Data Vault: Scalable Enterprise Data Modeling
Learn Data Vault modeling methodology for building auditable, scalable enterprise data warehouses with hash keys and satellite tables.
Posts tagged with #data-modeling
Kimball Dimensional Modeling: Star Schema Techniques
Learn Kimball dimensional modeling techniques for building efficient star schema data warehouses with fact and dimension tables.
One Big Table: The Denormalized Approach to Data Modeling
Learn how One Big Table architecture simplifies data pipelines by combining all attributes into single wide denormalized tables.
Slowly Changing Dimensions: History in Data Warehouses
Master Slowly Changing Dimension techniques including Type 1, Type 2, and Type 3 for maintaining historical accuracy in data warehouses.
Denormalization
When to intentionally duplicate data for read performance. Tradeoffs with normalization, update anomalies, and application-level denormalization strategies.
Document Databases: MongoDB and CouchDB Data Modeling
Learn MongoDB and CouchDB data modeling, embedding vs referencing, schema validation, and when document stores fit better than relational databases.
Graph Databases: Neo4j and Graph Traversal Patterns
Learn Neo4j graph database modeling with Cypher. Covers nodes, edges, social networks, recommendation engines, fraud detection, and when graphs are not the right fit.
Materialized Views
Precomputed query results stored as tables. PostgreSQL refresh strategies, indexes on materialized views, and when to use them vs views or denormalization.
Database Normalization: From 1NF to BCNF
Learn database normalization from 1NF through BCNF. Understand how normalization eliminates redundancy, prevents update anomalies, and when denormalization makes sense for performance.
Schema Design: Building the Foundation of Your Database
Learn how to design effective database schemas with proper data types, constraints, and relationships that scale with your application.