If the available data are accurate, they may contain hidden (unexplained and uninterpreted) information that can be deciphered and expressed formally (mathematically) in several ways. An in-depth analysis of data can explain, to a certain extent, how Earth system components work and evolve in time. However, raw observations can be noisy and difficult to read and interpret without a priori knowledge of the problem and adequate tools and methods. These challenges are common limiting factors and can cause frustration for even highly experienced data analysts. After data preprocessing, validation, and modeling, an initial interpretation of the data can be performed, and conclusions can be formulated. However, the virtual distance covered by the investigation path, from the stage of fieldwork or laboratory experiments to the final results, can be very long, with up to several hours or days spent on data collection, examination, clearance, preprocessing, transformation, and modeling. Some of these steps can be time-consuming and require substantial computational power and computer memory capacity.