by Roman Egger – Salzburg University of Applied Sciences, Innovation and Management in Tourism
While the field of Data Science (DS) continues to grow in strength and popularity, its repertoire of methods, including a wide plethora of various frameworks, software, and tools, is also increasingly advancing in parallel. As such, data scientists, researchers, and other users are not only faced with the challenge of keeping track of all the available solutions and alternatives on the market but also of choosing which tool is most suitable for each individual project. Furthermore, in addition to the requirements of having a solid theoretical background and understanding the broad range of methodological skills, it is also necessary to be able to use and apply these solutions in a correct and appropriate manner. In order to give the reader a rough overview of the available tools and their performance spectrum, a selection of software, platforms, and solutions for data science is briefly presented in this chapter. In addition, the authors have compiled a list of relevant software packages in relation to their respective content/chapter in a tabular list provided at the end.