Domino was started by three impressive veterans of the finance industry who wanted to empower data scientists and analysts with technology that accelerates their work and facilitates best practices.
Domino makes your data scientists more efficient by giving them “one-click” functionality for scaling their infrastructure and deploying their models (in Python, R, etc) without depending on IT or Engineering.
Think about that for a minute. If high performance engineering is eliminated – to a large extent or altogether – from testing and launching predictive models into production code, then data science teams all over the planet will be cheering.
There is such a shortage of “big data” engineers and data scientists that have both exceptional statistical and engineering skills, that Domino can solve a giant problem in the marketplace for the foreseeable future. It also facilitates best practices, keeping analytical work centralized and sharable.
Their company mission is to help data scientists focus on their analysis, without spending time building infrastructure or leaning on internal IT/engineering resources for support. They do that in three ways:
- Make it easy to use scalable infrastructure to run models faster
- Make it easy to schedule reports and share results with non-technical stakeholders
- Make it easy to “operationalize” models built in R, Python, etc. by deploying them as web services, so you can easily integrate them with existing software applications
For more about practical applications of Domino’s platform see the Stories page.
Domino currently works with some very well known consumer, financial services and insurance companies, and the platform can run on cloud hardware or on premise behind your firewall.
One FINAL FYI: Domino is one of the sponsors at Gigaom Structure Data in NYC next month, and giving away a couple tickets to the event: http://www.dominodatalab.com/gigaom