Hot on the heels of its $12M Series B funding in December, Trifacta recently announced the general availability of the Trifacta Data Transformation Platform. Based on its innovative Predictive Interaction™ technology, the Trifacta Data Transformation Platform uses visualization and machine learning to streamline and enrich user-level interactions with Big Data such as the type experienced by data scientists and business analysts. Trifacta’s Predictive Interaction technology features three components: (1) visualization of big data that empowers analysts to specify trends, values or analytics of interest; (2) interaction whereby the analyst responds to the data visualizations; and (3) prediction of the data transformations suggested by user interactions, with corresponding visualizations of the data transformation. The platform’s machine learning capability iteratively responds to user behavior to generate analytics of increasing value and interest. As a result, users can swiftly proceed from a raw, unprocessed archive of big data to incisive analytics and visualizations without the pre-processing, data cleansing and data transformation steps that are typically necessary to obtain deeper insights into about the data in question. The Trifacta Data Transformation Platform enables business analysts without scripting experience to derive nuanced insights about big data and additionally amplifies analyst productivity by means of its unique visualization and machine learning technology platform. Trifacta Customers include Lockheed Martin and Accretive Health, both of which remarked on the way in which the Trifacta Data Transformation Platform accelerates the data analysis lifecycle and streamlines user workflows. Trifacta’s technology is unique in the Big Data industry because of its focus on streamlining and enhancing the end user of big data analysis. Given the ubiquity of data visualization in the industry, much of the platform’s ability to differentiate itself will hinge on the sophistication of its predictive modeling and machine learning capabilities.
Trifacta today announced the finalization of $12M in Series B funding in a round led by Greylock Partners and Accel Partners. Trifacta, a data transformation provider, delivers a solution that helps customers standardize and transform data into a form that optimizes the degree of actionable business intelligence that can be derived from that data. More importantly, the solution features a user experience that enables analysts and data scientists to leverage machine learning to transform data as desired while minimizing the writing of scripts and the execution of complex operations on datasets. The Trifacta platform strives to deliver a highly intuitive user interface for transforming data that enables business analysts to engage data in highly sophisticated ways while concurrently improving the productivity of data scientists. As such, the solution tackles two, often overlooked problems in the data analytics space, namely, transformation of data into a useable form, and improving the productivity of analysts engaged in the work of that transformation. Trifacta’s data visualization functionality and algorithmic, machine learning-based mapping of user interactions with data works to understand, recommend and optimize workflows for interacting with data. In an interview with Cloud Computing Today, Trifacta CEO Joe Hellerstein noted that the solution is currently in public Beta amongst customers from a wide range of verticals, all of whom face the same problem of transforming their data into a form that facilitates development of nuanced, actionable analytics and visualizations. Today’s funding raise brings the total capital raised by Trifacta to $16.3M.
This Thursday, Trifacta came out of stealth mode by announcing $4.3 million in Series A funding led by Accel Partners, with additional participation from X/Seed Capital, Data Collective and angel investors Dave Goldberg, Venky Harinarayan and Anand Rajaraman. Trifacta’s mission is to “radically enhance productivity for data analysis” by delivering a solution catered to the human resources responsible for gleaning business significance out of data analysis. Based on the premise that the cost of skilled data analysts continues to rise while the costs of storage and computation become progressively lower, Trifacta intends to enhance the ability of analysts to more effectively manipulate, mine and derive insights from massive amounts of structured data. In an interview with VentureBeat, TriFacta’s co-founder and CEO Joe Hellerstein elaborated on the company’s mission as follows:
There is a lot of talk about engines and algorithms for unlocking value in data. But real value comes from the people who drive the analysis. The question is how you get data into the form where people can get some value out of it.
Similarly, Ping Li, head of Accel’s Big Data fund elaborated on his fund’s interest in Trifacta by noting:
The world doesn’t need another Hadoop or SQL company. The biggest problem with big data is around the ability to get information out of it. That gap is huge, and it’s not going to be solved anytime soon. This is really the soft underbelly of big data right now.
Hellerstein and Ping Li both point to the importance of facilitating access to business insights from Big Data in contrast to merely delivering an enterprise grade storage solution. Trifacta was founded as a result of collaborations between computer scientists at UC Berkeley and Stanford University. The company’s leadership team features cofounder Joe Hellerstein, former Professor of Computer Science at UC Berkeley, Jeffrey Heer, Co-Founder & Chief Experience Officer and Sean Kandel as CTO, whose Ph.D. dissertation research at Stanford University examined interactive products for manipulating data. CXO Jeffrey Heer is also an Assistant Professor of Computer Science at Stanford University, where he leads the Stanford Visualization Group. Specific details of the company’s solutions remain under wraps at present, though Trifacta’s website reports that the company is busily preparing details of solutions for public release while it gears up for a round of aggressive hiring.