It’s no secret that some people hear about Tableau’s passionate users and wonder what all the fuss is about. Back in June, in fact, one skeptical industry analyst tweeted to a Tableau fan, “Pal, you seem to have had a bit too much Tableau Kool-Aid.”
Tableau users I know just shrug. People who say things like that find passion for data suspicious, and there’s nothing you can do for them.
Then Tableau itself invited a delegation of industry analysts, most of them from the traditional end of BI, to its annual conference at the Encore hotel in Las Vegas. The company hopes for their blessing to make that leap across the chasm from early adoption to early majority.
My big question: Would the industry “influencers” and Tableau’s influential users play nice together?
I hang out with both groups, the doubters and the devoted. I do periodic retreats to TDWI and other events. I’ve also been an observer of Tableau since 2008 when I blogged that “Tableau is the new Apple.” I have no stake in Tableau’s success except that I think it’s a strong part of BI’s dream fulfilled, a bearer of fruit.
Experts can quibble over its limitations all they want to, but they must acknowledge one thing: It excites users. Few other tools do.
I spotted trouble on the first morning. In the opening keynote, CEO Christian Chabot had invoked one of his favorite themes: how Tableau would “change this tired, paternalistic BI order.” As usual, he got applause. To illustrate an anecdote about dairies, he pulled out a bottle of milk and poured himself a glass. Things were going well.
But about then, an industry expert tweeted from somewhere in the audience. He hinted at a suspicion of Kool-Aid: “It’s just a visualization tool with publishing capabilities.”
He might as well have asked what these 1400 or so nut cases were doing there, packed into that ballroom? Why, going by numbers from Tableau CMO Elissa Fink, did Experian send 17 people, Apple 19, and eBay 35? Did they come for the gambling, the shows, and a sweet sip of delusion?
Two special meetings with Tableau founders and the delegation of experts went better. As we sipped water from the Encore’s handsome tumblers, Chabot and fellow founders Chris Stolte and Pat Hanrahan talked about business plans and technology. Most of the influencers asked about the technology. We’ll have to watch their blogs for reactions.
Eventually, we left technology for more interesting, big picture questions. Neil Raden, of Constellation Research, asked how the company would grow and still satisfy the new demands of the broad new audience? Other technology vendors have stumbled on this. I asked a similar question: If they do as everyone expects and offer an IPO, how would their passion and vision endure under the new pressures?
The gist of both answers: They said they’re not doing this for the money, and they’ll continue to be driven by the same passion for a great tool, and that they’ll be guided by the same integrity. Cynics will scoff, but I believe them.
Meanwhile, out on “the street,” influential Tableau users expressed harsh opinions of the BI regulars.
One man with long experience in business intelligence and data warehousing, whose employer prohibits public statements, called the general class of BI experts “process junkies.” He said, “They don’t understand that I have this data and I want to understand what it tells me. It doesn’t fit.”
Similarly blunt: “I don’t care what these supposed experts think,” said Dan Murray, a longtime Tableau user and chief operating officer of InterWorks Inc, a fast-growing technology consultancy. The company is listed in the Inc. 5000, and it attributes much of its growth to database development and Tableau visualization.
“The BI people are back where we were a long time ago,” said Murray. “We’re past that.” To him, the people who really matter in data analysis now are the ones with passion for data analysis. He said, “Those are the superstars.”
Just who the superstars are marks the line between those who’ve had the “Kool-Aid” and the BI regulars. Most of the usual experts seem to live in the backend, where database administrators and other geeks rule. Back there, the game is all about process and data hygiene. The experts love to talk about all that, and only a few actually analyze data.
Up where the data analysts work, it’s all about analyzing data. They take seriously all the factors that the mainstream BI world does — such as data quality and data governance — but always with the end in mind, not as ends in themselves.
Ask them what they like about Tableau and their answers come down to one point: the thing gets out of the way and let them work almost as fast as they can think. It does so far better than any other data tool they’ve known. They feel that the tool is designed with them in mind — not for any purchaser, not for any security goon, and for not any consultant’s ego.
They are passionate. I had gone to dinner with a half dozen Tableau users when one wondered aloud about the Las Vegas airport’s on-time record. Someone had his laptop along, loaded with FAA data from an earlier analysis. We found seats in a bar near the casino and looked at the data. I don’t know of many others for whom data analysis beats ESPN.
We ordered beers.
Meta Brown says
Ted,
Please tell us more about these passionate users. What is their background – what kind of training and work experience do they have, what are their job roles? How would you characterize the fans?
Ted Cuzzillo says
Meta, thanks for your comment. I’m working on those answers. Ted
Jon Boeckenstedt says
I’m not an IT person, but an end user who needs to act quickly on data. And I’m not a “joiner” in the sense that any cult-like loyalty to Apple or any other product based solely on the cool factor is distasteful to me. Software is a tool, and it’s the best one I use right now.
In my presentation at the conference, I told of how a light bulb went off in my head when I saw a story about a 1950’s strike of elevator operators in Chicago: Remember when we needed elevator operators to push the buttons for us? Doesn’t that seem silly now? Can’t you walk onto any elevator and figure out how to work it yourself?
I think it’s an apt metaphor for Big BI: Using traditional, clunky, and job-focused structures, often laden with bureaucracy, to think about getting insight out of data. Using elevator operators when there is a self-service elevator to be had.
The mechanical part of creating reports and the intuitive, creative part of generating insights are both important, but the latter is far more critical. Tableau lets the people with the business knowledge generate the insight by giving them a powerful tool to do so, often eliminating the cumbersome and critical weeks between the need and the fulfillment.