Multivariate statistical analyses are used for reducing large datasets to a smaller number of variables, which explain main hydrogeochemical processes that control water geochemistry. Factor analysis (FA) allows discovering intercorrelations inside the data matrix and grouping of similar variables, i.e. chemical parameters. In this way new variables are extracted, which are called factors, and each factor is explained by some hydrogeochemical process. Applying FA to a dataset that consists of 15 chemical parameters measured on 40 groundwater samples from Serbia, four factors were extracted, which explain 73.9% of total variance in the analyzed dataset. Interpretation of obtained factors indicated several hydrogeochemical processes: the impact of sea water intrusions and volatiles in previous geological periods, solutes diffusion from the marine clay, cation exchange and dissolution of carbonate and silicate minerals.