Big data analytics — where vast troves of information are structured and used to help businesses gain more insights into their operations and customers, to develop new products, and to run more efficiently — are a cornerstone of how many tech-centric enterprises run their businesses today. Now the focus is on building solutions that the rest of the enterprise world can use, even if the business itself is not necessarily tech-centric. Today, an Israeli startup called Iguazio — which has built an “edge data” analytics platform targeting IoT, finance and other services that require real-time processing — is announcing that it has raised $33 million in funding to build out its service.
We understand from sources the company’s valuation is around $100 million.
Iguazio — a reference to Iguazu Falls, which itself is a reference to how big data is like a voluminous, fast-moving and complex waterfall — has been around since 2014, but has spent most of that time in stealth and closed beta.
It’s been a closely-watched and fruitful period for the company. Iguazio has to date raised $48 million and it counts a number of its investors as beta users. This latest Series B was led by Pitango Venture Capital, and others in the round included four strategic investors: Verizon Ventures, Robert Bosch Venture Capital GmbH (RBVC), trading platform CME Ventures and Dell Technologies Capital. Previous investors (from its $15 million Series A when it was still in stealth) that also participated in this round include Magma Venture Partners and Jerusalem Venture Partners.
Each strategic investor in this latest round points to verticals where Iguazio believes its business has the potential to develop, CEO and co-founder Asaf Somekh told me in an interview.
Verizon — which is making its first investment ever in an Israeli startup, part of its new operation in the country that launched a few weeks ago — hopes to build out a new business in IoT and telematics (partly to offset competition and declining growth in fixed and consumer-mobile services). Bosch is also one of the leaders in in-car systems. CME is building out its futures and options trading platforms to cover more and more data points. And Dell is, like many other hardware companies, looking for new revenue streams in services.
“Our investors fit very well with our direction,” Somekh said. “We are engaged with all of our investors to some degree.” He added that while there are no revenues yet, for the last year and a half “we have been working with companies and are on the verge of the first generally available product that will come out in a manner of weeks.”
The idea behind what Iguazio is doing is that it’s trying to provide a platform for businesses to engage with big data analytics in a way that will actually produce results with minimal headaches.
Somekh cites Gartner research that found that only one out of every 10 big data analytics projects in enterprises succeeds because of the lack of complexity and skills in the business to deploy and run them.
“As one of the largest telecom companies in the world, we witness the importance of real-time continuous analytics and the way it has become crucial across businesses. Yet, there are not many existing scalable solutions,” said Merav Rotem-Naaman, Managing Director at Verizon Ventures Israel, in a statement. “Iguazio is aiming to become a trusted partner for companies looking to use data to make real-time business decisions that improve security and operations. IoT data that improves decision-making and transforms business must get analyzed closer to the edge, whether it be a fleet of trucks or the monetization of mobile usage.”
While there are a lot of big data analytics services on the market today, Iguazio’s unique selling point is that it offers its services at the ‘edge’ — that is, close to the point of where processing is taking place.
For services in areas like the Internet of Things, this is an essential component of how these networks will develop: cloud-based processing can become too costly when you have a vast network of end points, but the end points themselves do not necessarily have the processing power to crunch numbers from across the rest of the network, as well as its own.
Edge computing is an area that a number of other companies are looking at: recall Cisco and IBM’s deal last year to integrate IBM’s Watson AI analytics into Cisco’s edge routers. Others in the area include the startup MapR.
Iguazio’s approach — providing a platform that makes using big data analytics simple for any kind of business, whether technical or not — falls in line with another trend that we’ve been noticing. If areas like big data analytics and artificial intelligence represent the next wave of computing, there has been a rush of startups coming out of the gates that are focusing on building ways to make that next wave more accessible.
Others in this vein include LiveStories, which is building a data ingestion, analytics, and visualization platform specifically aimed at civic organizations that might otherwise lack the in-house ability to do this kind of work themselves. Element AI, meanwhile, is ambitiously building an “incubator” aimed at both smaller startups that touch one of the many aspects of AI, and enterprises that want to have better access to that tech, to help them meet somewhere in the middle. Like Iguazio, both have raised funding in recent weeks to build out their services to meet demand.
Notably, the founding team at Iguazio have a strong track record when it comes to building tech companies and exiting them. Another co-founder is Yaron Segev, who started and ran flash storage company XtremIO, which sold in 2012 for $430 million to data storage giant EMC. (Dell’s investment here comes via the EMC connection.)
“Iguazio’s team has an outstanding track record of innovation and execution and we are delighted to back these stellar managers once again,” said Eyal Niv, Managing General Partner at Pitango, in a statement. “While the majority of big data deployments fail due to over complexity, iguazio’s platform has proven to be simple, fast and secure, making it exceptional for artificial intelligence and machine learning use cases. We’ve already received overwhelming feedback from beta customers generating actionable real-time insights with significant business impact.”