As I type this, Tableau Software's stock is up 20%, buoyed by earnings that dramatically outperformed expectations.
And by "dramatically" I mean doubling the expected non-GAAP earnings per share ($.14 instead of $.07), on the back of 63.5% revenue growth to $170.8 million.
Not too shabby.
The reason for that growth is simple: The world is exploding with bigger and bigger data, and Tableau makes that data digestible by the masses. Or, as Tableau CEO Christian Chabot expressed it on the company's earnings call, "We've made it easy for people to quickly answer their own questions with data."
But, Tableau won't be alone in making big data simple. Amazon also aims to do this, and is a clear and present danger to Tableau and its peers.
Tableau cashes in on the big data Gold Rush
There's no shortage of vendors to help enterprises tame their data, of course. In fact, Hortonworks, one of the foremost big data infrastructure vendors, announced its own earnings last week, and has seen its own stock rise 10% due to better than expected earnings and revenue.
But, Tableau is different.
Years ago, then Wall Street analyst (and current Aerospike executive) Peter Goldmacher argued that there are three classes of big data winners. The first are the companies like Hortonworks, Cloudera, MongoDB, and DataStax that lay the infrastructure.
The second, potentially bigger winners are companies like Tableau, that is, "the Apps and Analytics vendors that abstract the complexity of working with very complicated underlying technologies into a user friendly front end."
The third category is the enterprises that figure out how to put big data to use to transform their industries—companies like Uber. But, even these companies find value in Tableau and its ilk.
Again, following Chabot on the earnings call, he declared, "It's rare to find [a product] where IT professionals sit alongside of their business partners in finance and HR, operations, sales, and marketing...and cheer for the same product."
And he's right. Tableau has distinguished itself as a product that is useful across industries and across functions within a single enterprise. Or, as analyst Den Howlett notes, Tableau is solving "twenty-first century problems" by "allow[ing] people to easily visualize [their] data in new and interesting ways."
Even more succinctly, "Tableau will help make us smarter with data that, today, is hard for us to parse."
And yet...Tableau has a big blind spot.
All your data are belong to AWS
In the Q&A portion of the Tableau earnings call, Chabot was asked about the entry of Amazon Web Services into his BI market. Chabot batted it away, arguing that two things will hold AWS back.
First, and most importantly, "Most of these platform tied offerings are really fairly light and shallow and not particularly capable products. Most industry observers and outsiders will call them sort of 1.0 feeling products that lack basic capabilities and largely have a long road ahead of them."
Unfortunately for Chabot, AWS is innovating at a pace that this contention, even if true today, won't be so tomorrow. Remember when AWS compute and storage were only good enough for test and development use cases?
Chabot's second argument is even worse: "they tend to be optimized or exclusively used with the data from that platform provider themselves."
I say "worse" because, guess what? Increasingly enterprises are putting more and more (and more) of their workloads into AWS. GE is moving 90% of its workloads to AWS. Does Chabot think he's going to make a mint on the remaining 10%? Because AWS is introducing new BI/data analytics services at a frenetic clip, and GE isn't alone in its rising dedication to the public cloud giant.
This is the problem for Tableau and, really, any big data vendor. While AWS still represents a relatively Lilliputian slice of the overall IT pie, its appetite is huge. Taking a blase attitude toward the Amazon threat won't serve Tableau well.
- AWS now 10X the size of its competitors: Is the cloud arms race over? (TechRepublic)
- The public cloud just got a new poster child (TechRepublic)
- The machines are eating your BI, says DataStax CEO (TechRepublic)
- How non-IT pros get analytics faster than ever before (TechRepublic)
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.