Here is an interview with Florian Douetteau, founder of Dataiku, on how their tools empower data scientists, and how data science itself is evolving.
Dataiku develops a collaborative end-to- end software platform called Data Science Studio (DSS) that companies use to accelerate the development of in-house business and predictive solutions. It promises a significant increase in efficiency an productivity for the company’s data scientists, business analysts, and product managers.
Florian Douetteau is Dataiku’s Chief Executive Officer. Florian started his career at Exalead, an innovative search engine technology company. There, he led a R&D team of 50 brilliant data geeks, until the company was bought by Dassault Systemes in 2010 for $150 million. Florian was then CTO at IsCool, a European leader in social gaming, where he managed game analytics and one of the biggest European cloud setup. Florian also served as freelance Lead Data Scientist in various companies, such as Criteo, the European Advertising leader.
Here is my interview with him:
Ajay Ohri: Describe your journey as a data science startup. What was the reason for you deciding to make DSS.
Florian Douetteau: In 2012, my partners and I saw an opportunity: the data science market was (and still is) extremely fragmented. We’re living in a very interesting technological universe where lots of tools and options for working on and with data are available. Today, the challenge is more about applying the right tool and the right location and then tackling the complexity of having multiple storage systems and languages. For instance, you could prefer using Pig for some data munging, Hive for computations, Python or R for advanced modeling, ElasticSearch for search, Hadoop for large scale processing, and so on.
So we took a step back and looked at the big picture: what were we trying to solve and why? What existed and who else was trying to solve it. Then, we focused on the users. How could we solve the fragmentation problem of the data science ecosystem (for both proprietary and open source solutions) for them better than the rest? What weren’t those users getting from available solutions and how could we bring it to them intelligently? For us, that meant enabling our users, no matter their skill set or level of expertise, to collaborate while maintaining the freedom to use the tools and languages they know best.
Ajay Ohri: Describe your product- how does it help experienced as well as aspiring data scientists?
Florian Douetteau: Dataiku is guided by the belief that to succeed in the world’s rapidly evolving data ecosystem, companies – no matter their industry or size – must continuously re-invent & deliver innovative data products. With this in mind, our mission is to provide all organizations with the technological environment that will enable their teams to effectively dispense the data innovations of tomorrow. Dataiku’s approach to collaborative data science and machine learning enables these organizations to compete with the digital giants that have blossomed in the past decade.
Thanks to a collaborative and team-based user interface for data scientists and beginner analysts, to a unified framework for both development and deployment of data projects, and to immediate access to all the features and tools required to design data products from scratch, users can easily apply machine learning and data science techniques to all types, sizes, and formats of raw data to build and deploy predictive data flows.
Finally, without the hassle of connecting and drubbing tools, users of all experience levels can quickly learn and excel in languages like R or Python and discover what machine learning is really all about.
Ajay Ohri: What is user feedback from your customers.