Why tools, philosophy, and bright people matter for building tomorrow’s data platforms
Summary
At de Volksbank/ASN, we proved that Model Driven Data Engineering (MDDE) works in practice.
A key enabler was CrossTest, CrossBreeze’s automated testing framework, together with the open-source PowerDecomposer, which allowed us to extend PowerDesigner into a metadata-driven workflow.
The lessons from this project — and from other customers — directly inspired the development of CrossModel and CrossGenerate, modern tools built to replace legacy modeling environments and automate code generation.
This article highlights why CrossBreeze’s philosophy matters, and how it fits into the future of data engineering.
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CrossBreeze’s Philosophy
CrossBreeze is built on a simple but powerful idea: data engineering should be model-driven, not code-driven.
Their philosophy centers on:
- Shift from programming to modeling → Put the business and metadata at the core.
- Automation as default → If it can be generated, don’t hand-code it.
- Testing as a first-class citizen → Quality is not optional; it must be built in.
- Bridge business and IT → Models that capture business semantics are the real driver of sustainable platforms.
Tools in Context
- CrossTest: The first product we used at Volksbank. It embedded automated regression and functional testing directly into the data warehouse pipelines, making every release safer and more reliable.
- PowerDecomposer: An open-source solution that decomposed PowerDesigner models into metadata structures, enabling automation and governance. It was essential for filling the gaps left by PowerDesigner. 👉 PowerDecomposer
- CrossModel: Developed later, based on insights from Volksbank and other customers. It was built from the ground up as a modern replacement for PowerDesigner, Erwin, and other legacy data modeling tools.
- CrossGenerate: Created alongside CrossModel, this tool automates code generation directly from metadata models, bridging the gap between design and implementation.
Together, these tools form a closed feedback loop:
➡️ Model → ➡️ Generate → ➡️ Test → ➡️ Deploy → ➡️ Govern
Insights from Their Blog
CrossBreeze’s blog expands on these ideas with practical insights:
- Automation Made Practical: Articles on how model-driven frameworks reduce manual coding errors and speed up delivery.
- Business/IT Alignment: Stories about bridging the gap between data modelers and developers, ensuring models remain true to business rules.
- Testing for Confidence: A recurring theme is the importance of automated tests for trust in data, especially in regulated industries.
- Future of MDDE: Reflections on how CrossModel, CrossGenerate, and CrossTest can shape the next wave of metadata-driven platforms.
👉 Explore more here: CrossBreeze Blog
Why It Matters
In my view, CrossBreeze embodies the shift our industry needs:
- Away from heroic coding toward governed modeling.
- Away from ad hoc testing toward automated quality.
- Away from technology churn toward metadata as the foundation.
They don’t just provide tools — they provide a mindset. And in large-scale, regulated environments like ASN (De Volksbank), that mindset is the difference between delay and delivery.
Closing Thoughts
The future of data engineering is metadata-driven, model-first, and automated. CrossBreeze shows how to make that vision concrete with tools, philosophy, and a relentless focus on quality.
For me, their biggest contribution is not just technology, but the reminder that bright people, working with the right principles, can change how data engineering is done.\