Model driven data engineering

CrossBreeze’s Model Driven Data Engineering approach streamlines traditional, manual data engineering by using upfront metadata modeling to automatically generate schemas, transformations, and data pipelines.

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Traditional data engineering often involves repetitive manual work. Writing DDL scripts, configuring pipelines, and documenting data flows can be time-consuming and error-prone. At CrossBreeze, we introduced the Model Driven Data Engineering approach to streamline this process.
The idea is simple: by modeling all required metadata up front, you can generate much of the data solution automatically. CrossModel enables this by letting teams design data structures, flows, and logic in a structured, governed model. From this model, you can generate code for schemas, transformations, and orchestration.

Model driven data engineering

With CrossModel, you can:

  • Generate warehouse structures and ETL logic from models
  • Keep design, implementation, and documentation aligned
  • Iterate faster with consistent and versioned model outputs

See supported tools and code targets on the Integrations page.