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How BMW Group built a serverless terabyte-scale data transformation architecture with dbt and Amazon Athena
- BMW Group's Cloud Efficiency Analytics (CLEA) team developed a serverless data transformation pipeline using Amazon Athena and dbt to optimize costs and increase efficiency.
- Initially facing challenges with schema complexity and high query costs, the team adopted Athena, dbt, AWS Lambda, AWS Step Functions, and AWS Glue for enhanced development agility and processing efficiency.
- The architecture includes around 400 dbt models, integrates seamlessly with GitHub Actions workflows for automation, and employs incremental loads for better performance and schema management.
- The solution is organized into three stages—Source, Prepared, and Semantic—each serving a specific purpose in the data transformation process.
- Dbt's SQL-centric approach, documentation capabilities, testing framework, and dependency graph have significantly improved the team's agility in modeling and deployment.
- The use of Athena workgroups, QuickSight SPICE, and effective partitioning strategies have contributed to scalability and cost-efficiency in the data transformation pipeline.
- The architecture has reduced operational overhead, enhanced processing efficiency, and provided significant cost savings through optimized query executions and materialization patterns.
- With Athena's serverless model and dbt's incremental processing, the team achieved rapid model development, streamlined deployment, and improved data processing accuracy.
- The architecture is ideal for teams looking to prototype, test, and deploy data models efficiently while maintaining high data quality and reducing resource usage.
- The adoption of dbt and Athena enables BMW Group to manage growing data volumes effectively, optimize resource allocation, and achieve cost savings through efficient data processing approaches.
- This serverless architecture is recommended for teams aiming to accelerate data model deployment, enhance cost efficiency, and ensure accurate, high-quality data processing.
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