Trifacta Raises $12M For Platform That Uses Human And Machine Interactions To Prepare Data For Analysis

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Trifacta, a platform to prepare data for analysis, has closed a $12 million Series B round led by Greylock Partners and Accel Partners. The company has now raised a total of $16.3 million.

In an email interview, CEO and Co-Founder Joe Hellerstein said the company’s platform is designed for business analysts and data scientists to explore, manipulate and cleanse data for the purpose of analysis. The technology is based on research at Berkeley and Stanford that focuses on the interactions between humans and machines to transform data into something useful and meaningful. The process of this human-computer interaction is meant for the analyst and the machine to both provide insights based on the patterns in the information.

On the Trifacta platform, users work with visual data and smart suggestions, while machine learning methods analyze data and user interactions, Hellerstein said. The interplay makes this process of data transformation more accessible to business data analysts, while increasing the productivity of quantitative data scientists who can use the human-machine interaction to get through various types of data in a faster manner.

Hellerstein said use cases are for just about any industry — a large computing device vendor, for example, that has products in the field that are shipped back to the manufacturer so the behavior data on the device can be analyzed. The data tend to be complex and particular to the revision and configuration of each device. Trifacta’s platform allows the product divisions to do their own data transformation on the raw data logs and transform them into data that can be loaded into business intelligence and predictive analytics tools. The process gives the manufacturer the ability to do maintenance prediction, feature usage assessment, quantitative product design revision, etc.

Human-machine interaction is an emerging field that is gaining in popularity as the methods for analyzing data become more accessible. The complexity is lessening as machine learning and other advanced analytics practices get filtered through visual tools.

For example, Hellerstein pointed to the work of Mike Bostock at the New York Times who uses D3.js in his data visualizations that appear online and in the newspaper.  He originally developed D3.js with Trifacta Co-Founder Jeff Heer while the two were studying at Stanford. D3.js is a JavaScript library for manipulating documents based on data that allows for visualizations in the browser.

A company like Trifacta represents two trends, said Ronnie Mitra, an API architect, who I interviewed at API Days, a conference now taking place in Paris. The utility for data is illustrated in the way companies are driving more decisions by analyzing mass troves of information.

“The other trend is leveraging the UX to provide niche experiences,” Mitra said. “For a long time there was a focus on function, the things that programs do. “The pioneers of interaction design have started moving things up,” to the application level.

Trifacta is part of a new generation of companies that provide data-driven analysis for customers to do business intelligence, risk analysis and a host of other matters. The challenge for Trifacta is building a service that competes with a variety of different tools from companies like Informatica, Revolution Analytics and Pentaho.