Anaconda vs IBM Watson Studio

Anaconda is great for academic and private organizations that cannot afford more expensive Python/R package managers. Also, it is more appropriate for intermediate to advanced Python users--Anaconda can be somewhat frustrating for beginners, as it takes some practice to get comfortable with the workflow. I find it particularly useful for working in teams, because if everyone uses the same package manager, it is easier to troubleshoot issues and makes for reproducible research. For wealthier organizations, a premium package management system (with tech support) would be ideal. Anaconda is also great for people working independently on code development.

It's a fantastic environment for learning basic Data Science skills; working with insensitive, non-production data; and performing simple data visualisations. It is completely unsuited to enterprise production deployments requiring advanced auditing and security; sophisticated and transparent machine learning; complex analytics and custom data visualisations.

because we find out that DSX results have improved our approach to the whole subject (data, models, procedures)

The UI flawlessly merges this offering by providing a neat, minimal, responsive interface

From time to time there are services unavailable, but we have been always informed before and they got back to work sooner than expected

Never had slow response even on our very busy network

I received answers mostly at once and got answered even further my question: they gave me interesting points of view and suggestion for deepening in the learning path

The trainers on the job are very smart with solutions and very able in teaching

The Platform is very handy and suggests further steps according my previous interests

It surprised us with unpredictable case of use and brand new points of view

It helped us in getting from 0 to DSX without getting lost