DBT + Databricks in Production: Lessons From Scaling Analytics in Enterprise Environments
This article details the challenges and solutions for implementing dbt and Databricks in large enterprise analytics environments. It highlights how initial proofs-of-concept can mask complexities that emerge at production scale, particularly concerning cost optimization, governance, and auditability. The piece offers insights for data platform leads, analytics engineers, and architects on building reliable and cost-efficient data pipelines within these demanding contexts. AI
IMPACT Discusses the application of data analytics tools in enterprise settings, with indirect relevance to AI/ML workflows.