Highly Optimized Data Engineering Pipeline

Overview

Data collection in precision agriculture results in fragmented and messy data. This project focused on designing a highly optimized ETL (Extract, Transform, Load) pipeline to streamline the research process.

Data Sources Integrated

• Milking meters (Yield/Flow data)
• Rumen sensors (pH/Temperature)
• Accelerometers (Activity/Behavior)
• Environmental loggers (Barn conditions)

Pipeline Features

• Automated Merging: Combining data from disparate sources based on timestamps and unique IDs.
• Cleaning Algorithms: Robust error handling for missing values and sensor outliers.
• Readiness for Analysis: Outputting standardized datasets ready for immediate statistical or machine learning analysis.

Significance

This infrastructure significantly reduced the time spent on data preprocessing, allowing more focus on actual research and discovery.