Dear Clients and Friends,
The report found here gives our sense of the current m&a trends and deals in the Enterprise Data and Analytics sector that we follow and sometimes lead. Please click here for our October Enterprise Data & Analytics Report.
Data is only useful if it is actionable. In some cases it’s stale in a week; in others it takes days or seconds; and in the case of trading algorithms, military drones, and self-driving cars –it’s meaningful if it can be received, processed, analyzed, returned and acted upon within milliseconds.
Local computing sometimes can solve the need for speed; as long as you have enough local compute power; the source and consumer of data are local; and you can afford it.
Cloud computing, with its gigantic data centers spread around the globe, has no lack of compute power; is cost efficient; and is well suited for dealing with disparate data sources and distributed users – as long as milliseconds aren’t important. And then there is the New “New” thing: “Edge” computing. We don’t have the space here to fully explore Edge computing. But it’s coming (and in some cases, it’s already here) taking advantage of the cloud where possible, and at the same time putting compute power in locations that are closer to the user than the big cloud data centers.
Take self-driving cars as an example. They simply don’t have computing power “locally” to receive, process and use the massive amounts of data necessary to operate safely and efficiently in real time. Even small delays in updating road and weather conditions can result in longer travel times or taking wrong routes; delays in communicating with other vehicles could result in disaster. According to a recent report by Toyota, the amount of data transmitted between cars and the cloud could reach 10 exabytes a month by 2025. That’s 10,000 times the current amount. The cloud wasn’t designed to process that amount of data quickly enough for self-driving cars. The answer is “Edge” computing.
The recently announced merger of Cloudera and Hortonworks could result in a company that’s focused on providing building blocks for big data deployments. We are frequently amazed by the pace of innovation in this transforming world and are excited to work with companies that are taking advantage of them.
Current m&a values and trends as well as a few of the more interesting m&a transactions are reflected in the following report including:
- Slack Technologies (San Francisco, CA) raised $427mm in a Series H funding round at an implied valuation of more than $7.1bn from new investors,
- SurveyMonkey raised $180mm in its IPO, implying an enterprise value of ~$2bn and valuing the company at an implied 8.8x LTM revenue,
- Enigma Technologies (New York, NY) raised $95mm in a funding round led by New Enterprise Associates with participation from BB&T, Capital One Growth Ventures, MetLife, Third Point, Glynn Capital, Comcast Ventures, Crosslink Capital, Two Sigma Ventures and the Partnership Fund for NYC,
- OmniSci (San Francisco, CA) raised $55mm in a Series C funding round led by Tiger Global Management.
We have a team that will be heading to Money2020 in Las Vegas, October 21-24th. If you’d like to arrange a meeting there, please contact Scott Friedman at sfriedman@marlinllc.com.
Please find our full Enterprise Data & Analytics October Report here.
