Instruments often primarily designed for data collection produce rich curve and spectral‑based data, but their associated software typically supports only limited, domain‑specific analysis. Once loaded into JMP, even small changes in how the data is structured can enable far more flexible and interactive analysis.

This presentation shows how JMP is used interactively to structure instrument output into analysis‑ready formats using a workflow‑driven approach. Using nuclear magnetic resonance (NMR) spectral data as a representative example, we demonstrate how exported data can be quickly reshaped so it works naturally across JMP platforms.

Attendees see how different data structures enable interactive exploration in Graph Builder, targeted data reduction using PCA and covariate‑based selection, and predictive modeling in Functional Data Explorer (FDE), where curves or spectra are treated as functional observations rather than individual points. While NMR provides the example, the techniques apply broadly to curve and spectral‑based data from many types of instruments.