dbt for Data Transformation: Build Your First Pipelines

Effective data transformation is crucial for modern analytics, and dbt has become an industry standard for building robust data pipelines. This course will guide you from foundational concepts to building production-ready data transformation workflows, enabling you to deliver clean, trustworthy, and analytics-ready datasets. What you'll learn: * Understand core dbt concepts including models, sources, and directed acyclic graphs (DAGs). * Develop modular and maintainable dbt projects following modern project structure best practices. * Implement comprehensive data testing and documentation strategies to ensure data quality and discoverability. * Configure various materializations and optimize model performance for efficient data processing. * Apply incremental processing techniques to manage large datasets and reduce transformation times. * Build robust data pipelines, integrating dbt effectively within a modern data stack. * Practice writing SQL transformations and deploying dbt projects using version control principles. The course begins with essential terminology and setup, progressing through practical model development, testing, documentation, and advanced transformation patterns. You'll learn step-by-step how to construct a dbt project, from initial setup and model creation to implementing sophisticated data quality checks and deployment strategies. This course is designed for absolute beginners in data transformation and dbt, with no prior experience required. Start building powerful data transformation pipelines today.