How to Use Python In KNIME For Advanced Data Science Workflows

KNIME is data science platform into which advanced Python algorithms can be integrated. This workflow uses the both of best tools to analyse responses to a personality questionnaire.

KNIME is a visual coding platform for data manipulation and analysis which provides an alternative to the traditional text based data science programming languages, such as Python and R. The visual style of coding works well when developing a workflow that integrates with different data sources; where that data is manipulated and processed; and then either written back to storage or presented to the end user through interactive visuals.

Whilst it is possible to do all of these things in Python and R, KNIME offers a number of benefits:

1. The visual style lends itself to describing and self-documenting the workflow. It is clear where data comes from, what transformations are applied and where it goes.
2. The visual style is less intimidating and easier to grasp for those without experience of text based coding, allowing a much broader group of employees to engage in data analytics.
3. Integration with a wide range of data sources. This includes flat files, databases and cloud based services. This reduces the time needed to plug-in to data and start analysing it.