A collection of SQL and Python examples that run on the mimilabs data lakehouse
You can run these example scripts in two ways:
- Within the mimilabs data lakehouse environment
- By downloading and ingesting the raw data locally
All datasets used in these examples are publicly available. You can find their sources in the mimilabs data catalog.
The repository structure mirrors the data lakehouse organization:
- Top-level folders represent schemas
- Nested folders represent tables
- Each table folder contains example scripts demonstrating various use cases
These examples are created through collaboration between AI and human developers.
We believe that data's true value lies not in the data itself, but in its applications. Impactful use cases emerge from practical, well-crafted examples. While we're building an extensive collection of examples, our focus is on quality rather than quantity.
Here's how you can help:
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Try our examples:
- Sign up for mimilabs
- Test the existing examples
- Share your feedback
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Expand our collection:
- Adapt existing examples for your specific needs
- Create new variations for different applications
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Help improve our AI capabilities:
- Contribute to AI development for evaluating example effectiveness
- Help us build AI tools that enhance dataset understanding
- Assist in developing AI that maximizes dataset potential
Together, we can unlock the full potential of open data!
This project is licensed under the Apache 2.0 License