We use anaconda just as a python distribution on Windows. I think if you want a real data analytics setup which works well on all individual platforms then it's

We use anaconda just as a python distribution on Windows. I think if you want a real data analytics setup which works well on all individual platforms then it's best to just build a docker-compose file. I was given a Dataiku presentation in New York in September and I liked it. My concern with such tools is that companies buy them thinking they are a 1 shop solution for analytics. For instance, how does Dataiku work with AWS/S3 Athena? Or how does Dataiku work with github? Maybe it works very well, I don't know, but evaluating those tools can take months. A "raw" python setup is, I think, an initial good first step as it forces teams to deal with all the architecture from the very beginning and it works because it integrates with everything. When you buy from a vendor you put yourself in a contract situation that could make it very hard to iterate to a final solution that actually works for the company. Open source doesn't have those problems.