Data transformation startup Trifacta Inc. today said it has raised $48 million in new financing from a group that includes several customers.

The seven-year-old firm, which bills itself as a provider of tools for “data wrangling,” or wrestling messy data into usable form, has raised a total of $124 million. The funds will be used for product development and geographic expansion.

The inclusion of customers New York Life Insurance Co., Deutsche Boerse AG, Telefonaktiebolaget LM Ericsson and Columbia Pacific Advisors LLC on the list of investors is a testament to the interest the company has aroused among large enterprises, said Trifacta Chief Executive Adam Wilson (pictured).

“In each case they reached out to us to have a conversation about investing in a subsequent round,” he said. “This lined up with our objective of making sure that this round brought in investors who would help us in significant ways beyond just investing.” Other participants in the funding round include Google LLC, Accel Partners LP, Greylock Partners, Cathay Innovation, Ignition Partners LLC and Ridge Ventures. 

Trifacta’s Wrangler product tackles the extract/transfer/load problem that is common to many big data initiatives. This process of cleaning and normalizing data prior to using it can overwhelm data scientists and frustrate data lake initiatives. Born out of research at Stanford University and the University of California at Berkeley, the Wrangler software was originally built for the desktop and given away free. The commercial version debuted in 2012 and Trifacta said more than 10,000 companies have now adopted it.

Wrangler uses machine learning to scour data, identify likely modifications and make changes automatically or flag them for human attention. The software also provides a variety of data quality metrics as well as meta-tags and shared models. Originally released for use in on-premises data centers, the Wrangler products are now being enhanced for multicloud environments.

The large representation of financial services firms on the investor slate indicates high demand for data transformation products, Wilson said. He cited Deutsche Boerse’s initiative to record stock transaction data that used to fall on the cutting room floor and harmonize it with external factors such as news feeds and social media to understand how cultural factors drive trading patterns. “If the data is poor, you’re not going to be able to create algorithms that work on that information,” he said. “You need to transform it into something that you can use.”

New York Life is working with Trifacta to create insurance products and risk models at a fine level of segmentation in order to tailor insurance products for individual members, Wilson said. “We saw an opportunity not just to make them successful, but to replicate that success across the insurance industry,” he said. As a new investor, New York Life “gets input into how the product evolves and we get insight into the challenges they’re facing.”

Wilson spoke with theCUBE, SiliconANGLE Media’s live streaming studio, at SiliconANGLE’s Big Data SV event last year:

Image: theCUBE