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Intelligent Data Model for Equipment Data

A research project with AstraZeneca turning unstructured manufacturing equipment data into a queryable model the business could act on.

Role
Undergraduate researcher, Purdue's Data Mine
Built
November 2025
Stack
Data modeling, Unstructured data extraction, Python

The problem

AstraZeneca had equipment data that existed but wasn’t usable: unstructured, and therefore invisible to anyone trying to ask a question of it.

What we built

An Intelligent Data Model that transforms that unstructured equipment data into accessible formats, so the business can generate insights from it and build further enhancements on top.

The prior year’s project

The same Data Mine partnership with AstraZeneca ran a different project the year before, during the 2024-2025 academic year: replacing paper-based Quality Control logbooks with a digital system. Write-up: Digital Quality Control Logbooks.

Context

Delivered through The Data Mine at Purdue University, a corporate-partnered undergraduate research program, during the 2025-2026 academic year. The AstraZeneca project page has the poster and the final video walkthrough.