A comprehensive collection of advanced SQL data pipeline implementations showcasing modern data engineering patterns and techniques using PostgreSQL. This repository demonstrates production-ready solutions for complex analytical workloads with real-world use cases.
You can view more analytical queries related to this project here: SQL-analytical-patterns
Features:
- SCD Type 2 implementation for actor career tracking
- Season-over-season performance analysis
- Data change detection and version management
Real-Time Analytics
- User Engagement Tracking: Monitor user activity patterns across devices
- Performance Monitoring: Track application and website performance metrics
- Behavioral Analysis: Understand user journey and interaction patterns
Historical Reporting
- Trend Analysis: Long-term performance and growth tracking
- Comparative Analytics: Year-over-year, season-over-season comparisons
- Cohort Analysis: User retention and engagement over time
Data Warehousing
- Dimensional Modeling: Proper star and snowflake schema implementations
- Data Quality Management: Automated deduplication and validation
- ETL Pipeline Automation: Incremental data processing workflows