It has been years since Gartner first reported that enterprises were going ga-ga for big data, without having clear plans as to what to do with it. Today ,it may still be true that some enterprises continue to struggle with putting their data to use, but for many, big data is really a question of how fast they can accelerate rather than whether they should start.
That's one lesson from Cloudera's latest earnings report, which shows the big data company significantly expanding its footprint within large enterprises. With over 60 enterprises now investing more than $1 million each year with Cloudera, we've clearly moved into the expansion phase of big data projects.
But first, the data
To put this Cloudera customer data in context, it's worth rewinding the company's results a bit. Overall, Cloudera added 132 Global 8000 customers in the last year, and 32 in the last quarter. Big companies are betting on Cloudera and its competitors like Hortonworks, not to mention more established vendors like IBM.
But where things get more interesting is when we look at the biggest spenders among these big companies. A year ago, Cloudera could claim just 30 customers spending more than $1 million each year. A quarter ago, that number had jumped to 50. This quarter, Cloudera has doubled its million-dollar customer club, booming from 30 to 60. Along the way, it has hiked subscription software revenue 50% to $301 million. That's a lot of cash, and it gets even bigger if we add in the money generated by its competitors and peers.
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Even more tellingly, Cloudera saw its total gross margin bump up from 71% a year ago to 75% today. As the company's CFO Jim Frankola noted on the earnings call, "Cloudera's continued gross margin expansion is due to subscription software revenue growing faster than services revenue as well as the increased efficiency of our technical support organization."
In other words, Cloudera is having to spend less on services to help companies embrace its data infrastructure, suggesting a growing familiarity and maturity among larger enterprises with big data. Clearly, enterprises are finally investing significant cash in big data, moving well beyond the pilot phase and into production.
This isn't to say that it's smooth sailing from here on for Cloudera or any other big data vendor. Though the company has managed to expand its footprint among existing customers, it has found the cost of sale to be higher than expected.
SEE: 60 ways to get the most value from your big data initiatives (free PDF) (TechRepublic)
The reason? As much as enterprises want to embrace their data, and as much as they've matured in their ability to do so, it's still way too hard. Mike Olson, Cloudera's chief strategy officer, made this point on the call: "The challenge is [that new data infrastructure involves] brand new techniques: enterprises don't understand how the algorithms work [or] which ones to choose and don't know how to operationalize [and] apply those algorithms to their business problems."
One thing that will help with this is if vendors stop pitching buzzwords and instead focus on tangible techniques and techologies for solving tangible business problems. Auto manufacturers want safer, self-driving cars, for example. Rather than waving hands around and talking algorithms, big data vendors need to show these target customers how to apply big data tech to solve that problem.
They also need to find new ways to get their tech into the hands of technical users who can make sense of the technology for their business buyers. That is, they need to make big data technologies more accessible to developers, the gateway into the enterprise. By making big data infrastructure less about tech and more about real-world use cases, and by making it more accessible to developers, companies like Cloudera will make more money by helping enterprises continue to expand their adoption of big data.
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Matt is currently head of the developer ecosystem at Adobe. The views expressed are his own, not those of his employer.
Matt Asay is a veteran technology columnist who has written for CNET, ReadWrite, and other tech media. Asay has also held a variety of executive roles with leading mobile and big data software companies.