To Code or Not to Code with KNIME

Many modern data analysis environments allow for code-free creation of advanced analytics workflows. The advantages are obvious: more casual users, who cannot possibly stay on top of the complexity of working in a programming environment, are empowered to use existing workflows as templates and modify them to fit their needs, thus creating complex analytics protocols that they would never have been able to create in a programming environment. At the same time, these visual environments serve as an excellent means for documentation purposes. Instead of having to read code, the visual representation intuitively explains which steps have been performed and – in most environments at least ‒ the configuration of each module is self-explanatory as well. This enables a broad set of intuitively reusable workflows to be built up capturing the data scientists' wisdom.