DataikuI am working with a prospective customer currently using Dataiku. Dataiku seems to be more of an enterprise product but need to be able to speak directly to how JMP is different than Dataiku. Anyone with experience with this product and can speak to how we can differentiate ourselves? Thanks.
Re: DataikuPerhaps you have seen the recent thread about the NXP Hackathon. FWIW, 'DataIku' is the tool that NXP seems to have standardised on. As a member of the judging panel, I saw several demos. Others involved with this project may have their own commentary, but my summary would be that, although JMP could co-exist (synergistically . . . ) with DataIku, it could never replace it.
Re: DataikuWe just ran into them at another customer. My impression is pretty similar here. Different tools for different tasks. Limited analytics with the data science bundle, which is an extra cost, and allows machine learning and data mining through Python. Seems like everything would need to be configured and developed for a specific use-case, vs. the general problem solving tool that is JMP. In this customer interaction, it was actually suggested that Dataiku could be used for data cleanup and warehousing tasks ahead of JMP analysis as well (connecting to live data sources) so this certainly isn’t and either/or conversation.
Re: Dataiku@Emmanuel_Romeu may be able to provide some additional information on the customer interaction that I was speaking about above. It was my take-away from the call that there is some overlap, but the use-cases organizationally would be different for Dataiku and JMP. JMP Live has a bigger overlap with Dataiku, especially with plans for data refresh capabilities server-side in JMP 17 and beyond.
