You can find out more about metabolomics in general via this introductory course provided by EMBI.
This workflow deals with mass spectrometry data (specifically from Waters instruments - please feel free to contribute content for other instruments) in which there are no pre-defined molecules we are looking to compare between two or more classes (groups) of samples. While the type of mass spectrometry chosen will influence which molecules are more likely to be detected (and there is no truly untargeted metabolomics!), untargeted metabolomics looks to form ideas of what is differing between two or more classes (groups) of samples.
The outcome of untargeted metabolomics can serve as a great exploratory analysis, on which to build the hypotheses for further, more targeted, mass spectrometry. For example, if you find that a lot of flavonoid compounds are putatively identified as differing between drought stressed tomato plants and well-watered controls, you will be able to justify subsequent (costly and time consuming) LC-MS-MS for specific flavonoids.
Untargeted metabolomics produces huge quantities of (sometimes three dimensional) data. It can be overwhelming. Hopefully this guide will help you navigate what all the data (and jargon) means. It is worth noting, however, that you will be left with a lot of unknowns. So try and be clear about what your data processing is trying to acheive - you are going to address the question:
❓ Which compounds might be responsible for the difference in metabolomic fingerprint between the classes (groups) of samples?
⚠️ You will not get a definitively quantitative difference or unquestionable compound identification from this workflow. You will get a good idea of which compounds are a good bet for further study.