Enterprise Tech 30: Domino Data Lab

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In this series, Nasdaq spoke with Nick Elpin, co-founder and CEO of Domino Data Lab, which was recently named to Wing Venture Capital’s Enterprise Tech 30 list.

What prompted you to start Domino, and what opportunity did you see?

My co-founders and I spent many years building software to help quants inside a large hedge fund accelerate their research and collaborate better. We saw how big of an impact data science had when it was used to drive the heart of a business, and when researchers were enabled and empowered with great technology. As we talked to other companies scaling their data science teams, we saw how much time and energy they were wasting (dealing with dev ops, reinventing the wheel, reproducing past work), and we wanted to give them a platform to unleash their full potential. 

How quickly are Fortune 500 companies adopting data science and machine learning?

Very rapidly. One of the striking trends we’re seeing is rapid adoption in industries that aren’t typically considered early adopters. For example, while we’ve seen data science and ML for years in finance and life sciences, we’re now seeing more urgent adoption in manufacturing, telecommunications, retail and transportation. We are working with one of the large automakers who described their “pent up demand for data science across the business”: they see so many opportunities for data science to impact their business that they can’t grow their data science team fast enough to keep up.

Of course, with that urgent need to scale a data science organization, companies run into another set of problems. What we see across the enterprises we work with is that when you reach scale, the biggest challenges aren’t about finding a faster algorithm — rather, the big challenge is about how to help large teams collaborate and work together more effectively, to ensure increasing returns on investment as the team scales.

How are people using Domino to help in the fight against COVID-19?

Two ways:

First, with data science teams across the country now working from home, every team is a distributed team. As difficult of a shift as that is, we are very proud of the fact that Domino makes remote collaboration so much easier. Having data science work in a central collaboration platform facilitates distributed work and has made the work-from-home transition easier for all our customers.

Second, many of our customers are in the life sciences space, and several of them are using Domino to research COVID-19 treatments; other customers of ours in the finance space are using Domino to build models to predict spread and growth.

We know it’s a small fraction of the impact that health care workers on the front lines of the pandemic are having, but we’re proud to be contributing, in some small way, to helping our customers through this crisis. We also recently announced that we’re offering complimentary access to organizations that are advancing the collective understanding of the COVID-19 virus, its spread, and approaches to lessening its destructive effects across the population. Doing what we can to assist health and life science organizations during this outbreak means a lot to us.

What role can data science play in helping to keep people informed?

Data scientists have a skillset that integrates statistical methods, programming, and data visualization — that gives them a unique ability to tell stories in visually compelling ways, that help people understand complex and subtle topics.

We’re seeing this first hand with the COVID-19 pandemic. Exponential growth is an un-intuitive concept for most people. And for those of us who aren’t on the frontlines of the pandemic, it can be hard to appreciate the sense of scale and urgency we’re facing.

Data scientists and data journalists have stepped up to create valuable visualizations and analysis to give the broader population and more visceral understanding of the crises. Some of my favorite examples of the work from John Burn-Murdoch at the Financial Times and the interactive dashboards that the team at Johns Hopkins has built. The NYTimes also has a wealth of innovative and insightful data visualizations.

What does it mean to your company to be listed on the Enterprise Tech 30?

It’s a validation of our focus on enabling enterprise data science organizations, and it reminds me of how proud I am of how Domino fuels the progressive change that our customers are making in the world through their innovative research. Enterprises have a huge set of use cases and applications that benefit from the predictive learning efficiencies of data science, many of which have real impact on people’s daily lives. Examples include managing the supply chain to meet demand, automation to improve customer experience, helping reduce insurance rates, or developing new medicine (several of our customers use Domino to research COVID-19, in fact). I am incredibly optimistic and excited about the impact that data science will have on the world over the coming years.

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