Today was a big day for Big Data and analytics, as data discovery and visualization darling Tableau Software made good on its filing for an initial public offering. The company's shares were issued today on the New York Stock Exchange, under the ticker symbol "DATA." Wow.
Tableau offered 8,200,000 shares of its Class A common stock at a price to the public of $31.00 per share. The shares closed up almost 64% above that initial pricing today, their first day of trade. Tableau now has a market capitalization of $2.9 billion.
I had the opportunity to speak today with Tableau's CEO and co-founder, Christian Chabot, and I discussed with him matters relating to Hadoop, data scientists, the business intelligence space, its business models, and what's next for Tableau.
Don't spend it all in one place
To start, I asked Chabot what the IPO-derived capital would be used for. His answer was that the IPO was more about raising public awareness of Tableau, and the credibility of the company, than it was for expansion per se.
"Tableau everywhere" is what Chabot says is the company's next frontier. He explained that Tableau's revenue is currently derived from a Windows-only, on-premises-only offering and one with limited market awareness, to boot. So there's a lot of growth opportunity to go.
Product or stack?
While that's all well and good, we have to assume that Tableau will expand its sales force and quite possibly its product portfolio. So I asked a few questions around those topics.
With Tableau's growth as a private company, and its now seemingly quite successful IPO, it has set a very high bar for itself. I pointed out to Chabot that this has all been built around what is essentially a single product, and so I asked what Tableau would do to keep the momentum going.
First off, Chabot corrected my assertion that Tableau is a single product, insisting that Tableau Desktop, Tableau Server and Tableau Public are quite separate. I suppose this comes down to semantics; to me, three different editions that are all geared to data discovery don't constitute separate products, but certainly they are marketed separately, and that does count for something.
I peristed in exploring the possibility of new products from Tableau though, as most of its BI competitors offer a full stack of products that cover data integration, master data management, data quality, conventional reporting, and more. Chabot explained that there's little reason to match everyone with a full BI stack simply for the sake of conforming to the market category. But he also told me that the company is interested in diversifying into new product areas for which Tableau is seeing significant customer demand. Chabot said that a data integration offering is of particular interest to Tableau.
Declaring independence, and neutrality
But if Tableau remains mostly focused on data discovery and visualization, it begs the question of whether it will be acquired by one of the BI stack vendors that is weak in that area (and compared to Tableau, many such vendors are). Chabot insisted that Tableau will remain independent, explaining that such independence allows the product to remain a Swiss Army knife that connects to virtually any relational, Big Data or analytical data source, and how that benefits Tableau customers greatly.
Certainly, Tableau customers are a happy bunch, as I noted in my report from the Tableau Customer Conference last year. Chabot believes strongly that Tableau's undiluted dedication to self-service is what drives customers' passion, and that it also put Tableau well ahead of its BI competitors that offer self-service capabilities as a mere option, if at all.
Data science, for the layman
Having just participated in ZDNet's Great Debate, on the need for data scientists this week, I asked Chabot what he thought about the issue. Not surprisingly, Tableau's CEO feels that we are too reliant on specialists, and that expanding this "priesthood of people" doesn't get us past the bottleneck. Chabot said that the complicated and developer-intensive nature of the vast majority of data technologies is what underlies Tableau's success.
With that complexity in mind, I asked Chabot about Hadoop. The quintessential Big Data technology is clearly popular, but hardly something one thinks of when the self-service, agile and empowerment themes that Tableau identifies with are invoked.
How did Chabot reconcile the success of self-service with that of a complex tool like Hadoop? He explained that Tableau sees Hadoop at many customers, but almost never sees it as a standalone platform. Chabot's implication was, I think, that people want to use Hadoop, but they want it to meld with the data warehouse, BI and transactional database technologies they have been using for some time. Chabot would tell you that Tableau facilitates some of that integration, and he'd be right.
I will just point out that 2013's trend of BI - Big Data convergence shows no sign of slowing. Tableau's ticker symbol of "DATA" doesn't have "BIG" in it, and it doesn't need to, because the market need around data of all types is even bigger.