Thanks to technical advances the acquisition of high throughput data has become comprehensive and affordable, but the challenge remains in the analysis of the generated bulk of data. Integrative approaches for omics data analysis allow for deeper insights than the evaluation on a single omics level. Especially the labor-intense interpretation of metabolomics data was supposed to be facilitated by the integration of other omics levels. As a result an association between genotype and metabolic phenotype could be established for 19 accessions of A. thaliana by linking the absence of specific secondary metabolites in root exudates to premature stop codons in genes encoding biosynthetic enzymes. In this thesis, further selected examples in plant biochemistry demonstrated the importance of a custom-made analysis for integrative research questions.