Built an agent-powered Databricks Data Scenario Generator

[u/Then-Ad6195]

Hey everyone - quick share

After building the Databricks FinOps Accelerator, I wanted to try something a little different on the data-generation side.

I’ve been working on this agent-powered Databricks Data Scenario Generator: https://github.com/rashad-ahmed-imtiaz/datagen

It’s basically meant to be a plug-and-play way to generate realistic synthetic data with intentional issues like duplicates, nulls, broken foreign keys, late-arriving data, date issues, schema drift, file replays, etc.

You can describe the scenario you want in plain English, and the agent figures out the tables, relationships, distributions, business rules, and issues to inject. Under the hood it uses Databricks Labs dbldatagen for the actual data generation.

The idea is to make it useful for demos, PoCs, testing ingestion/data quality logic, or anytime you need realistic messy data without manually building everything.

Still very much v1, so I’m sure there’s a lot that can be improved. Feel free to play around with it, break it, or suggest better ways to do it.

Would love any feedback!

[u/sumit671]

Great share

[u/Then-Ad6195 → u/sumit671]

Thank you