@aryaman_sharma this is a good question and I have attached two threads (with additional articles) and a link to a presentation by the KNIME CEO about the ‘philosophy’ behind KNIME.
The basic question is: how does one want to structure their data analytics processes and how should be involved. If you are Google and you have 10k highly trained people on standby to develop your tasks in every programming language available then maybe you will not use KNIME. But if you are a mid-size company with limited resources and want all your departments to have easy access to such tools - and maybe even want them to work together and share ideas and solution. Then KNIME is for you.
The same if you are a large company and you have a broad community and want all your people to speak the same language and work on a common platform then KNIME also is for you.
With people heavy into Coding I sometimes have the impression they so not want to use KNIME because it might make their work look too simple. Instead of pages and pages of (hopefully) ‘magic’ code you have a workflow that sort of documents itself and you can comment and other people can understand. Or it does look really AI-heavy if you spend hours on managing Python dependencies and yaml configurations instead of just loading an extension. And sometimes the management level is not fully aware of these challenges and just does want something with code.
In this regard KNIME sometimes is either stuck in the middle or in the perfect place - depending on how you see it.
With the advance of LLMs the skill of coding might spread and people might be less inclined to use a low-code tool. I just hope this will still be happy once they have to maintain the code.
I personally like to mix KNIME for ease of workflow and automation and access with some tasks that are very specific and can be done with R and Python.
If it is just for you: just use what you like. If it is for a company: best you have a strategy how to really include all stakeholders and give them the right tool and also make sure they can all use it - so not to loose the information and collaboration and expertise which is key to the success of data analytics, machine learning and the use of AI.
“The greatest data science books ever” by KNIME CEO Michael Berthold
(starting 07:00) “One hippo, all alone, calls two hippos on the phone.”