"KNIME® Analytics Platform is the leading open solution for data-driven innovation, helping you discover the potential hidden in your data". Sure! But what does this really mean? This section surfs the data science process, to get from raw data to report, predictions, or other interesting results. Indeed, the data science process is not a linear process, composed a fixed number of steps, but rather an iterative process demanding optimization and strategy changes at any time.
The data science cycle - previously known as the data analytics cycle and officially known as the CRISP-DM cycle - therefore is an iterative process to create, optimize, and finally deploy analytics models. The units below give a summary of the general cycle first and a description of the single phases afterwards.