🧩 This is the starting point of the Grocery Retail – Driven by Data series, focusing on turning Excel “spaghetti” into structured, normalized data. It lays the foundation for the data integrity, modeling, and strategy challenges that follow.

🧭 **Rules – Challenge 01 Spaghetti → Schema**

This is an educational and prototype competition created to explore the process of building real-world data challenges on Kaggle.  
It is not an official or prize-bearing competition. Participation is open to anyone for learning and collaboration.

This is the first challenge in the Grocery Retail – Driven by Data series. Like the others, it is educational and open for experimentation. No prizes or formal rankings apply.

1️⃣ **Conduct**

All participants must follow the [Kaggle Code of Conduct](https://www.kaggle.com/community-guidelines) and [Terms of Service](https://www.kaggle.com/terms).  
Be respectful, cite external sources appropriately, and share constructive feedback with others.

2️⃣ **Data Usage**

The dataset provided is for educational and demonstration purposes only.  
You may download, transform, and share derivative work for personal or academic learning, but no commercial use is implied or permitted.

3️⃣ **Collaboration**

Teams and discussion are encouraged.  
Public sharing of general approaches, code snippets, or schema, transformation, and data-structuring ideas is welcome.  
Do not share direct solutions or private datasets that would invalidate learning goals.

4️⃣ **Submissions**

Since this challenge focuses on schema design and documentation rather than leaderboard accuracy:  
Submissions may include `.zip` folders, `.ipynb` notebooks, or `.sql` files.  
Evaluation will be manual and qualitative.

5️⃣ **Timeline**

This challenge is currently in prototype mode and will remain open while materials and data are being refined.  
No prizes, deadlines, or rankings apply at this stage.  
Future versions may evolve into formal scored competitions as data complexity increases.

6️⃣ **Acknowledgment**

By joining this project, you acknowledge that participation is voluntary and intended for educational experimentation and public learning.

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*This challenge sets the groundwork for Challenge 02 – Errors → Integrity, which focuses on detecting and repairing data issues for trust and reproducibility.*

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