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⚠️ Sample data for demonstration purposes. Methodology and code reflect actual production implementation.

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📝 OVERVIEW

Automated data cleaning and transformation pipeline that processes 100K-3M records, reducing preparation time from 2 hours to 15 minutes (87% reduction).

🎯 BUSINESS IMPACT

• Feeds 8 dashboards and 10 recurring analyses • Saves ~10 hours per week of manual work • Improved data consistency and accuracy

🛠️ TECH STACK

Python (Pandas, NumPy) | Parquet | Excel | CSV

🔑 KEY FEATURES

✅ Reads multiple CSV and Excel files from different sources ✅ Automated data quality checks and validation ✅ Handles missing values, duplicates, and outliers ✅ Feature engineering and derived attributes ✅ Optimized Parquet output for fast querying ✅ Scalable to millions of records

💻 CODE

View on GitHub

📊 RESULTS