Dataiku has announced raising $28 million in a Series B round led by Battery Ventures, with participation from FirstMark, Serena Capital, and Alven.
The Series B round brings the total amount raised by the New York City-headquartered data science software company to approximately $45 million.
Dataiku said the funding will be allocated across three areas: Development, marketing, and recruitment.
It plans to double its headcount to 200 employees across its offices in London, New York City, and Paris over the coming months, and add connectors to deep learning frameworks to its platform.
Founded in France in 2014, Dataiku offers a "collaborative" platform, called Data Science Studio (DSS), with connectors to data sources, visual data preparation, and prepackaged machine-learning algorithms.
Previously data scientists would have to take historical data that tells a particular story and then train algorithms to be able to predict the future -- a process that could take weeks or months. With DDS, they can simply upload their data and select parameters, and the platform automatically trains and evaluates different machine learning models.
"The platform enables [data scientists and data analysts] to automatically connect with systems such as Hadoop, prepare the data in a very visual manner, and also do machine learning -- meaning leveraging data to forecast something or classify something -- automatically. The platform lets you compare different machine learning approaches and optimise them in an automatic manner," Florian Douetteau, CEO at Dataiku, told ZDNet.
Customers from industries such as ecommerce, finance, and healthcare are using DSS to build predictive dataflows to detect fraud, optimise internal logistics, and predict future maintenance issues, Dataiku said.
GE, L'Oreal, AXA, and HostelWorld are among Dataiku's customers.
"Our driving philosophy at Dataiku is the idea that everyone should be able to contribute or gather insight from data science," Douetteau said.
"We adhere to this because, in today's world, we know that the most competitive data-driven organisations are the ones that make the most of all of their data, and the most effective way to do this is to empower people to use the tools they know best."
Douetteau admitted one of the biggest challenges multinational enterprises face today is "reusing analytics", such as from one country to another or one product to another.
"You have those new analytics approaches that start working in an organisation, and the challenge is to scale that ... to build a strategy from one product or one location and apply it globally inside your organisation," Douetteau said.
"The ability to actually use analytics, to make it into a factory or machine approach, where you just reapply, globally this is a great challenge for organisations."
Dataiku has doubled its revenue every year since its founding, Douetteau said.
Dataiku is among a wave of data science software companies to close funding this year; Domino Data Lab -- described as the "Github for data science" as it offers a centralised environment where data science and quantitative research teams come to work -- announced raising $27 million in April in a round led by one of its hedge fund customers, Coatue Management.
In February, Austin, Texas-based startup Data.World -- a social network, discovery tool, collaboration platform, and data repository -- raised $18.7 million, bringing its total investment to $32.7 million.
The following month, DataRobot, which automates machine learning, announced it had raised $54 million, bringing its total investment to $111 million.