Analytics Engineering with SQL and DBT : Building Meaningful Data Models at Scale

This practical book shows data analysts, data engineers, BI developers, and data scientists how to create a true self-service transformation platform through the use of dynamic SQL.

With the shift from data warehouses to data lakes, data now lands in repositories before it's been transformed, enabling engineers to model raw data into clean, well-defined datasets. DBT (data build tool) helps you take data further. This practical book shows data analysts, data engineers, BI developers, and data scientists how to create a true self-service transformation platform through the use of dynamic SQL. Authors Rui Machado from Monstarlab and Helder Russa from Jumia show you how to quickly deliver new data products by focusing more on value delivery and less on architectural and engineering aspects. If you know your business well and have the technical skills to model raw data into clean, well-defined datasets, you'll learn how to design and deliver data models without any technical influence. With this book, you'll learn:What DBT is and how a DBT project is structuredHow DBT fits into the data engineering and analytics worldsHow to collaborate on building data modelsThe main tools and architectures for building useful, functional data modelsHow to fit DBT into data warehousing and laking architectureHow to build tests for data transformations