The criticisms of the talk are valid, but overlook probably the biggest counterexample to the (cool) tools presented here: Tableau. Its dominating many areas

The criticisms of the talk are valid, but overlook probably the biggest counterexample to the (cool) tools presented here: Tableau. Its dominating many areas of data analysis, yet the terms of service prohibit any scripting or API access to the formation of the XML that compose the .twb workbooks. The user is limited only to GUI clicking, none of which can be stored. So I think its fair to say "You Can't Do Data Science in Tableau," even though its a useful tool and well implemented as a reporting tool. To me it seems a bit of a trap to build proficiency with Tableau and get locked into a closed enterprise product, I'm seeing a lot of data engineers at my company getting sucked into what is essentially a "tableau developer" role.