Build an open data lake architecture with dbt Cloud and Starburst Galaxy

The integration of dbt Cloud with Starburst Galaxy enables the creation of an open data lake architecture, allowing data engineers, analytics engineers, and data analysts to efficiently build, test, and document data pipelines without the need for extensive data migration. This collaboration supports the use of open-source technologies, providing flexibility for businesses to choose between building or buying their data architecture solutions. By leveraging Starburst's capability to federate multiple data sources, users can combine data from various origins, such as AWS COVID-19 data, Snowflake databases, and TPC-H datasets, into a cohesive data lakehouse structure. The process involves reading, cleaning, and optimizing data through different layers—a staging layer for initial data collection, an intermediate structure layer for transformation, and an aggregate layer for final data preparation. The integration simplifies the management of data permissions and enhances accessibility for data consumers, who can view and manipulate aggregated data through role-based access control. The tutorial provided demonstrates setting up a project using dbt Cloud and Starburst Galaxy, showcasing the ease of creating and managing complex data pipelines with these tools.