“In Collaboration with... Everything!"

“Profiling data, explaining problems, and suggesting fixes — all offline, all in code."

“Zero ETL” might sound like someone waved a wand and made all your ETL jobs disappear. But what's the real story?

A real-world story of how a data migration looked perfect in design but unraveled under real data load, proving that data never lies.

Beyond the traditional data pipeline engineering, this is a fundamental shift in how we build, own, and ensure trust in data.

Learn how to turn Great Expectations into a Python-based DQaaS with Flask, enabling reusable, automated data quality validation.

Why traditional approaches no longer work — and what a resilient data strategy looks like