From Scattered Test Files to a Structured Database

The problem

A precision electronics manufacturer had test data spread across files in many locations, and needed to store, track, and report on it accurately.

What we built

We studied the data they collected, found the patterns, and designed a relational model to fit. Configurable Python scripts now create a new database automatically for each new product, so adding a product never means designing a database by hand.

A round-robin import then worked through thousands of new and existing files, bringing years of scattered results into one consistent structure, and it keeps new results flowing in.

What it made possible

With the data finally in one place and one shape, the company could start asking questions across products and over time. That foundation now supports a company-wide analysis application, built as a separate project.