Can you trust your data?
In this talk we’ll take a real life use case where the flexibility desires and time have gotten the best of it. What happens when you deal with “freedom” data? How to go from this to a better future?
It is a technical talk how we recognize changes are desired, validation is required for trust to grow. Pydantic and pytest are used to work towards a solution where failing fast is a main objective.
This talk addresses a problem every engineer recognizes but rarely talks about openly: the slow accumulation of unstructured, inconsistent data that quietly undermines your automation efforts. “Freedom data” - the kind that grew organically because it was convenient at the time - is everywhere.
What makes this talk compelling is that it doesn’t stay in the problem space. It walks attendees through a real-world journey using practical tools like Pydantic and pytest to build trust in data incrementally. The “fail fast” philosophy gives teams an actionable mental model they can apply immediately.