With the increasing computational power, an abundance of data has become available in different research fields. To handle such an ever increasing amount of data, tools such as data management, machine learning and/or workflow managers receive increasing attention. In the field of materials science such approaches allow to investigate a wide range of materials and their properties in a systematic manner. The workflow managers are used in high-throughput calculations leading to the generation of huge amount of data. Although, high-throughput calculations are limited by the structure size. Structures with >10^3 atoms are limited by the computational resources. Researchers use the generated data and/or intelligent data mining as an input to machine learning techniques to investigate material properties, beyond limitations imposed by computational resources.