Foundations of Analytics Engineering: dbt and Snowflake

The modern data stack has changed how organizations handle information, making analytics engineering a highly sought-after skill. If you want to move beyond basic analysis and start building robust data pipelines, this course is your starting point. You will learn how to design, test, and deploy data transformations using industry-standard tools. By working through practical written exercises, you will build a foundational analytics project from scratch, establishing a solid understanding of modern data modeling. What you will learn: * Understand the core principles of the modern data stack and analytics engineering. * Configure and manage a cloud data warehouse environment using Snowflake. * Build modular data transformation models using dbt and SQL. * Implement data quality tests and documentation to ensure reliable pipelines. * Apply modern version control and fundamental CI/CD practices to your data workflows. * Practice transforming raw datasets into clean, business-ready models. The course begins with essential terminology and the foundational concepts of cloud warehouses and data transformation. From there, it flows into step-by-step written tutorials where you will structure and deploy a complete analytics engineering project. This course is designed for beginners and data analysts looking to transition into analytics engineering. No prior experience with dbt or Snowflake is required. Start reading today to build your expertise in the modern data stack.