Many crucial measurements in the semiconductor industry involve determining the root cause of an electrical failure, often requiring the capability of extracting microstructural and chemical information with nanometer resolution [1]. The microanalysis is achieved by stepping the focused probe over the region of interest in STEM mode and recording an EDX and EELS spectrum at each pixel. Even for relatively modest image sizes, the resultant spectrum-image may consist of more than 10,000 spectra. With such large data sets, the prospect of manually inspecting and quantifying each spectrum in real-time is impossible and even automatic background modeling followed by peak area integration over selected spectral regions-of-interest can be excessively time consuming. Other methods to extract useful physical information include “fingerprinting” characteristic ELNES shapes to known compounds or bonding environments, multiple least squares regression to a relatively small set of suspected components or peak-fitting to model systematic changes in electronic density of states.