Domino Data Lab

Make data scientists more productive

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NickMakerHiring@nelprin
Hi there, I’m a Co-Founder of Domino and built a large part of the product, so I wanted to chime in. First, to address the question about why we don’t offer self-service trials: Domino is a broad platform designed for sophisticated quantitative research workflows. Its flexibility is a strength, but can also make it difficult to discover the full set of features and best ways to apply them. So when someone wants to try the platform, we like to show them how best to leverage Domino for their actual use cases — hence, our preference for a “Request a Demo/Trial.” Our goal is to partner with our users so they get the best experience, not to put artificial barriers in place. Anyway, @bentossell feel free to shoot me an email at nick@dominodatalab.com and I can set you up with an account if you want to try it. Second, as to why we made Domino… We see a lot of hype in the analytics space about products that promise you “insight from your data,” or that sell “something something something big data” (when most people don’t even have big data, btw!). Instead of trying to automate insight, we wanted to empower data scientists, amplifying their impacts rather than trying to reinvent their tools and workflows. (As an analogy: Github and Heroku don’t build software for you or give you a new programming language or IDE; instead, they make engineers more productive and help teams follow best practices.) We’ve found that approach resonates with sophisticated organizations where this type of work is really core to the business, i.e., where modeling and quantitative analysis is critical to a company’s revenue and competitive advantage. For example, Domino is used at leading insurance, pharmaceutical, manufacturing, and finance firms; and we work with In-Q-Tel, which brings new technology solutions into US government intelligence agencies. Those organizations tell us that Domino makes their data scientists more productive and facilitates best practices — collaborative, reproducible, compoundable research — across teams and organizations. Thanks for posting about us here, btw! Happy to answer any other questions.
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Eddie WhartonHunter@eawharton · Data Scientist, Dinner Lab
This is a great product for Data Scientists. It makes it easier to collaborate with other technical and non-technical users. Python or R models can be deployed as an API and thus productionized much easier. It offers scalable computing via AWS. I checked out their demo and concluded that the team I work on is currently too small to need this. As a data scientist, I can say that this is something I want to get once my company's size and challenges justify it.
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Ben Tossell@bentossell · newCo
"Request a Demo" - usually means expensive... I like testing a product myself first to see if I can get the hang of it, then worst case scenario... I then ask for a demo.. I think this day in age, the default should be "Try it > Succeed > Done" or "Try it > Fail > want a demo?"
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Eddie WhartonHunter@eawharton · Data Scientist, Dinner Lab
@bentossell yep. Exactly what I went through. It seems like a fantastic product, but was just too much. Unfortunately, most products for data scientists and analysts tend to be pricey :(. A lot of the other ones I've looked didn't even seem to be good or particularly differentiated. What I liked about Domino is that they help me use the language (python) and environment (Jupyter) that I am already using to get more value. I don't have to learn a new language or UI to get value.