This course analyzes advanced architectural patterns for modern data warehousing, focusing on Massively Parallel Processing (MPP) systems such as Snowflake, BigQuery, and Redshift. The content addresses high-throughput data ingestion, complex modeling techniques including Data Vault, and query performance tuning on distributed systems. You will implement solutions for data partitioning, materialized views, and automated governance. The material prioritizes technical implementation and architectural decision-making for engineers scaling data platforms beyond terabyte-scale datasets.
Prerequisites SQL & Warehousing Experience
Level:
Architectural Design
Design distributed storage systems using separation of compute and storage principles.
Performance Tuning
Optimize query execution plans through pruning, clustering, and materialized views.
Advanced Modeling
Implement Data Vault and dimensional modeling strategies for evolving schemas.
Data Governance
Automate role-based access control and row-level security policies.