After disappointing investors in the last couple of quarters, big-data pioneer Cloudera Inc. today managed to win some of them back with a favorable third-quarter earnings report.
In its third quarter since going public in April, Cloudera reported a loss before certain costs such as stock compensation of $23.2 million, or 17 cents a share, cutting the loss from a year ago by half. Revenue jumped 41 percent, to $94.6 million.
Analysts were expecting an adjusted loss from the company, which sells machine learning and data analytics software and services to manage huge amounts of data across computer systems, of 24 cents a share on $91.3 million in revenue, both at the midpoint of Cloudera’s own forecast three months ago.
Cloudera Chief Executive Tom Reilly (pictured) said on the earnings conference call with analysts that the company had won more new large companies in the quarter. “The large enterprise customers were of high quality and commenced with larger deal sizes than usual,” he said, adding that more than 50 companies are spending more than $1 million annually with Cloudera, accounting for half its subscription revenues.
“Our financial model is exhibiting consistent operating leverage as we march toward operating cash flow break-even,” he said in prepared comments. Although the Palo Alto, California-based company’s net loss was a sizable $56.6 million, up from $44 million a year ago thanks to high stock compensation costs post-IPO, its operating cash flow dwindled to $2.4 million from $32.5 million a year ago.
The company also made more progress on subscription revenue, a key metric because subscriptions are steadier than traditional software licenses. It rose 48 percent from a year ago, to $78.1 million. It’s now 83 percent of total revenue, up 4 points from last year.
Cloudera also issued a new forecast for the current quarter and the year. For the fourth quarter ending Jan. 31, it’s forecasting an adjusted loss of 22 to 24 cents a share on revenue between $97 million and $99 million, or up 33 to 36 percent. That’s better than analysts’ expectations of a 26-cent loss on $97.3 million in revenue.
For the year, Cloudera is looking at an adjusted loss of 82 to 84 cents a share on revenues of $361 million to $363 million, again better than Wall Street’s projected loss of 94 cents on revenue of $358.7 million.
Thanks to all that, shares were rising about 5 percent in after-hours trading. During the regular session, shares had closed up 1.7 percent, to an even $16 a share.
Up to now, investors have been unwilling to pay up for Cloudera’s topline growth. Despite outpacing estimates in the two quarters since it went public, investors haven’t been thrilled with those two quarters. After the first-quarter report, they knocked the stock down 16 percent the next day. Shares fell about 2 percent the day after the second-quarter report.
Investors are continually watching for signs of when Cloudera will become profitable, though its main publicly held rival Hortonworks Inc. is still losing money and privately held MapR Technologies Inc. is also likely in “growth mode” as well. Each is dependent to varying degrees on using freely available open-source software, so making money has always been a question mark. But it may get tougher yet as big cloud computing providers such as Amazon Web Services Inc., Microsoft Corp.’s Azure and Google Cloud Platform offer potentially more integrated data services.
Chief Financial Officer Jim Frankola said Cloudera is about four to six quarters away from breaking even on an operating cash flow basis.
Cloudera has been working to broaden its offerings. In September, Cloudera acquired Brooklyn-based machine learning research firm Fast Forward Labs and appointed co-founder and CEO Hilary Mason the larger company’s vice president of research. Cloudera co-founder and Chief Strategy Officer Mike Olson said at the time that he wanted to supplement the company’s application of machine learning and deep learning neural networks to “practical business problems.”
“We’re very focused on winning in the machine learning and AI space,” Reilly said.
(Siliconangle.com)
No comments:
Post a Comment