Shift Exchange Email Parser
What It Does
A municipal facility's shift exchange process was entirely email-based with no structured data. Parsed 293 raw .msg email files, extracting operator names, shift times, equipment readings, and operational notes into a fully normalized Excel spreadsheet with 4 tabs (151 sludge shifts, 142 wet shifts, plus equipment status views). Built a React dashboard on top of the data for visual analysis. Verified 3,709 individual data points with zero discrepancies against source emails.
Key Features
- Parsed 293 raw .msg email files into structured data
- Extracted operator names, shift times, equipment readings, and operational notes
- Normalized Excel spreadsheet with 4 tabs (sludge, wet, equipment views)
- React dashboard for visual analysis
- 3,709 data points verified with zero discrepancies
Why I Built It
The facility had no structured data from years of email-based shift exchanges. Parsing it unlocked analysis that was previously impossible.
What I Learned
Learned how to parse unstructured email data at scale and normalize it into clean, analyzable datasets. Built experience combining data engineering with frontend visualization.