Classical approaches from the world of data warehouse and business analytics have little to do with what we understood by mass data processing just years ago: Data volumes are orders of magnitude larger than they were a few years ago, interesting data is often unstructured, and at the same time its evaluation is to be carried out ever faster, especially in the environment of machine learning and deep learning. This is where the theories, procedures and tools associated with Big Data and Data Science are intended to provide support.
