Opera Solutions Lands Industry First with $84M for Big Data Innovation
Opera Solutions, a big data software maker (contrary to Opera Software, the developer of the web browser), just announced one of the biggest funding rounds in the history of this industry. The company secured $84 million in a first round of funding led by Silver Lake Sumeru, with participation from Accel-KKR, Invus Financial Advisors, JGE Capital Management, and Tola Capital. Morgan Stanley was the financial advisor.
Opera has a line-up of products that are all based on its Vektor analytics and signals processing platform. The firm didn’t come up with anything particularly original, but it puts a big emphasis on performance and RoI – which was evidently enough to convince VC to inject a huge amount of capital into Opera.
Arnab Gupta, founder and CEO of Opera Solutions gave some insight into this topic, and how the Company delivers this type of efficiency.
“Opera’s core value lies in turning Big Data into Small Data – that is, using advanced machine intelligence to extract valuable signals and patterns from massive data flows and turn them into a stream of analytically enriched guidance brought to the front lines of our customers’ businesses.”
Apsalar, a social analytics firm, also closed off a round of funding this week. The San Francisco-based company raised $5 million for its SaaS platform designed for Android and iOS app publishers that are looking to optimize their marketing. Last year, Apsalar received $800,000 from 500 Startups, Mark Goines, Morado Venture Partners, Founder’s Co-op and Seraph Group.
Another fresh big data update is the launch of We are Cloud’s Blime 3.0 at the DEMO fall conference. The latest version of the cloud-based, SMB-oriented business intelligence app allows users to create a language, file and metadata-agnostic query from within its web interface, and more.
VCs have been flocking to the big data market in recent times. Platfora for example raised $5.7 million in Series A funding, which Wikibon looked at in depth here.
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