Currently, extra virgin olive oil, virgin olive oil and lampante olive oil are classified using physical-chemical analyses and a sensory analysis of fruitiness and defects, which is carried out by expert panels. This manual analysis is nowadays considered to be controversial and therefore analytical methodologies, which may be automated to classify these samples, are needed. In this work, we propose using an analytical platform based on two orthogonal techniques to determine the flavour components perceived in the mouth and the components contributing to the olive oils (OOs) aroma, respectively. For the former, capillary electrophoresis with ultraviolet detector (CE-UV) and high-performance liquid chromatography with UV or fluorescence detection were explored. The CE-UV analysis provided better results with the developed chemometric models (principal component analysis, linear discriminant analysis and k-nearest neighbors method). While for the latter, headspace (HS) - gas chromatography coupling with ion mobility spectrometry (GC-IMS) was selected due to the easy applicability of this technique to classify OOs. Then both techniques, CE-UV and GC-IMS, were selected to be integrated into one analytical platform. The potential of using both complementary/orthogonal techniques was demonstrated using high-level data fusion of CE-UV and GC-IMS data.