I understand that Python is the basic stepping stone in Data Analytics programming side & I must learn upto certain extent of Python (if not expert) to make a career in Data Analytics. However, recently I observed, in Azure Machine Learning Studio, entire machine learning coding job has been simplified just as module drag & drop. With good understanding on Data Science-machine learning,one can easily manage the modelling with zero knowledge on Python (or any other language) coding. That is what I understood however being newbie in this area I am not confident if I oversimplified things & my understanding is correct or not. Is Python coding knowledge still required? Am I missing something? Even in any Data Analytics course, I see a special placeholder is kept for Visualization using Python (like graph plotting), but there also I see Tableau, MicroStrategy PowerBI or Qilkview which are much easier to use & I don’t know if I will still need to use the visualization library & code from Python to visualize my model output or data pattern. Could any of you help with your expert opinion ?
Getting confused in this Data Science ocean is pretty obvious.
You should not readily rely on drag and drop shortcuts, if you want to build a career in this field, You are supposed to be a developer ( producers, innovators) if you practice any domain( Data Science/Analytics in this case).
If you just know drag and drop . then You are a consumer, not a producer. They are being developed to ease the hectic process for non experts. And, You can link the rest of things, by now, i guess!
BI tools are moreover used for Presentation tasks, at the end of your model production.
Its not recommended to do viz on these tools, while going through the problem code, itself, It will just consume more time, nothing else.
BI tools are very useful, and one must learn them; but, to be able to present your results to a non expert user.
I hope this will clear out your doubts.