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-warehouse
Data Warehouse Architecture: Building the Foundation for Analytics
Learn the core architectural patterns of data warehouses, from ETL pipelines to dimensional modeling, and how they enable business intelligence at scale.
ELT Pattern: Transforming Data in the Data Warehouse
ELT flips ETL by loading raw data first, then transforming in the warehouse. Learn how modern cloud platforms enable ELT at scale.
Joins and Aggregations: SQL Patterns for Data Analysis
Master SQL joins and aggregation techniques for building efficient analytical queries in data warehouses and analytical databases.
Kimball Dimensional Modeling: Star Schema Techniques
Learn Kimball dimensional modeling techniques for building efficient star schema data warehouses with fact and dimension tables.
Lakehouse: Best of Both Worlds in Data Architecture
Understand how lakehouse architecture combines the scalability of data lakes with the reliability and performance of data warehouses.
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.
Snowflake Schema: Normalized Dimension Design
Explore snowflake schema design, where dimension tables are normalized into related sub-tables, reducing redundancy and enabling shared reference data.
Star Schema: The Workhorse of Dimensional Data Modeling
Discover why star schema remains the dominant approach for analytical databases, how it enables fast queries, and when to use it versus alternatives.