This project demonstrates the implementation of a comprehensive analytics engineering pipeline using dbt (data build tool) as the primary transformation layer. The pipeline showcases modern data engineering practices including ELT methodology, dimensional modeling, automated testing, and business intelligence visualization.
Repository: Analytics Engineering with dbt
The project focuses on transforming raw NYC taxi trip data into business-ready analytics tables using dbt’s modular approach, implementing both dbt Cloud and dbt Core workflows, and creating interactive dashboards with Looker Studio.
• Analytics Engineering: Bridging the gap between data engineering and data analysis with software engineering best practices • ELT vs ETL: Leveraging cloud data warehouses for in-database transformations • Dimensional Modeling: Implementing Kimball’s star schema methodology for analytical workloads • dbt Fundamentals: Models, macros, packages, variables, and testing frameworks • Data Governance: Testing, documentation, and deployment strategies • Business Intelligence: Creating interactive dashboards and visualizations
