Analytics Engineering with dbt: Build Modern Data Pipelines

The world of data analytics relies on clean, well-structured data. Analytics engineering with dbt empowers you to transform raw data into actionable insights, efficiently and reliably. By the end of this course, you will be proficient in using dbt to build, test, and document data models, setting a strong foundation for a career in modern data teams. What you'll learn: * Understand the core principles of analytics engineering and its role in the modern data stack. * Configure your dbt development environment and initiate your first dbt project. * Build robust data models and transformations using dbt's SQL and Jinja templating. * Implement comprehensive data quality checks and tests to ensure data reliability within dbt projects. * Apply best practices for organizing dbt projects, managing dependencies, and documenting data assets. * Practice developing modular and maintainable dbt codebases for scalable data solutions. This course guides you from the core principles of analytics engineering to practical dbt project development. You'll progress through setting up your environment, writing transformations, and implementing robust data quality practices. This course is designed for beginners with a basic understanding of SQL who want to enter the field of analytics engineering or enhance their data transformation skills. Start building your expertise in modern data transformation today.