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.

Most people shopping for business intelligence tools think they’re sophisticated, observes a sales person who often represents a large vendor in TDWI exhibit halls. Most of these people are deluded.

He may sound harsh, but he observes all this not bitterly but with good humor.

“They buy [BI] like anything else they buy,” he explains. “They put out a bunch of RFPs and go through this whole process and stuff, and eventually they buy the one that’s maroon.”

Over years, he has identified the top three reasons people buy, and the underlying motivation:

1. Career. The chosen tool decides the career of those who will learn it, massage it, and become co-dependent with it. Greed guides the choice; a good choice may ensure steady, lucrative employment for decades to come.

2. The boss’s choice. The boss says, “Buy that one.” Buyers fear defying the boss and like the boss’s power to give status. The blessed few may seem sexy, at least to themselves.

3. Default. They buy one brand and only that brand. They say, “We’re an Oracle shop” or “We’re an IBM shop,” and for them that’s reason enough. These irk this sales person.

The brand loyalists are the ones who seem to irk him the most, even though his brand often benefits from their foolishness.

Even the brand’s high cost can’t shake their trust. “A lot of people assume that more money means more quality and less risk. No, it doesn’t!” he says.

“They buy this big, fancy thing that no one uses.” Instead, many would be better off with a less expensive brand that delivers almost all of the name brand’s features. The left over funds should be spent on training.

The reason many shy away from training? They’d have to admit that there’s ramp-up time. “It’s kind of the Sarah Palin view: ‘Do we really need sophistication?’”

Users I interview for case studies tell me good stories. But most come with a poison pill: you can’t write it because it’ll embarrass someone. Just try getting it through the rounds of approval.

The smart marketer’s answer: Make up a composite!

If, as Financial Times columnist Gideon Rachman writes, fiction is the best way to understand Libya under dictator Muammer Qaddafi, then it just might work to understand the drama within organizations.

How much do you really understand from news accounts from Libya? Before the current crisis, most news emphasized Muammer’s weird style of dress, his ranting speeches, and his “voluptuous Ukrainian nurse.” Here at home, case studies emphasize rational and unnamed executives weighing pros and cons and coming up with insight and decisions. The corporate story is all so safe and pure you find yourself hoping the nurse appears.

The average case study’s best hope is to be marked “present” and forgotten. Fiction — once set free with the clear label of “composite” — has freedom to imagine and dramatize. It is best at the subtlety you need for insight.

Obviously, you wouldn’t use nasty stuff. That stains everyone. But use the stuff that’s merely too much for the squeemish.

Here’s my rant: BI is made for stories. Each success is a story, starting with “we didn’t know” or even “we were so screwed up, we couldn’t even…” The story meanders through “we searched and tried.” The stories worth blasting from the roof tops end with the details behind “now we know, and we’re this much more profitable.” Everyone knows and understands composites.

By the way, I think the part about the nurse is true.

Why should the smart people have all the fun with year-end predictions? You can issue your own! At this time of year, even hopeless nitwits can seem smart.

Once you set up a blog — any free service will do — all you have to do is throw together your trends. Keep these easy-to-use techniques in mind.

• Re-use last year’s trends. Does anyone really believe that 2010′s trends sat down in December for a cosmo and never stood up again? You can safely predict that this year’s trends will be next year’s, too.

• Search in Google for your industry’s name and “trends.” Take notes, rewrite a little bit and, boom, you’re an expert.

• Water the evergreens. For 2009, someone predicted, “Data interpretation will become a significant challenge for new BI users.” Will become? Can you imagine fewer business people having trouble interpreting data no matter what year it is?

• Follow in the draft of top vendors. Competition cyclists know that the easiest place to ride is just inches behind another rider. See where Oracle, IBM say they’re going and point in that direction. If a gang of marketing departments push an idea, it’s guaranteed to find at least a few new customers.

• Quantifying is risky but, done cleverly, it adds credibility. Just make sure your numbers can’t be verified. One clever expert sees 15 chiefs of analytics being hired in 2011. Bingo! The mere presence of a number, any number, gives the feel of certainty. Even if someone wanted to count, how would they do it?

• It’s good to be vague, but better to be incomprehensible. Suppose your crystal ball shows video becoming a big deal in 2011 (as if it weren’t already). Don’t just write “video,” as one hapless analyst did. Instead, pile on enough mumbo jumbo to let readers feel smart for having understood anything at all. Those who’ve tried to read 50 or 100 words will tweet about your “great” predictions.

• Aim for the horizon. Don’t let yourself be bound by others’ definition of “year.” If your vision fails to come true in 2011, you’re just that much further ahead of your time.

Above all, you must enter to win. After the first weeks of January, normal standards set in. If you feel like a fraud, remember that last week’s predictions are like last night’s eggnog. All people remember is the party, and all your readers will remember is your name.

How do you know when the business intelligence industry goes on break? It’s when Scott Humphrey goes fishing. He’s the man with the industry’s “golden Rolodex” to whom vendors, industry analysts, and press call to catch a story or to release one. The only news now is that last week the man behind the news took his brother and his nephew for a week of catch-and-release steelhead fishing on the free-flowing John Day River, four hours east of Portland. Cell-phone reception caught them now and then, and their phones “made noises,” but no one answered. That’s release.

Tableau Public’s score so far reads like one of those old McDonald’s marquees: 4.5 million people have visited data visualizations hosted by the site, says Tableau Software VP of marketing Elissa Fink.

More than 30,000 visualizations — “vizes” — have been published. The most popular of all, says Elissa, have been the ones about homes, personal budgets, and leisure. One of her own favorites is a local real estate blog, Seattle Bubble. “I wish I could have seen blogger Tim Ellis’s data in Tableau Public before I bought my house.”

Another favorite of Tableau staff, who are said to have a healthy contingent of foodies among them, is about cows and their milk. Vizzer Kate Golden at Wisconsin Watch charted the number of cows over the last 80 years in Wisconsin with the gallons they produced. Dairy farmers have 47 percent fewer cows today than at the peak in 1944 and ’45, and they squeeze three times more milk out of the cows they do have. In a YouTube-like moment, vizzer Carpe Diem responded. He mashed in milk prices. They’ve fallen, though it’s unclear how much; the viz fails to note whether the prices are adjusted for inflation.

The visit count keeps accelerating. Past growth feeds more growth. The big names that have joined in help, such as USA Today, The Seattle Times, and CNN Money. There are also influential bloggers like Mish’s Economic Blog and Infectious Greed also pull in visits. But the highest growth rate is among sports bloggers, such as pistonpowered.com and school bloggers like Gothamschools.org.

The “beef” — as in “where’s the beef?” — is whether Tableau Public really is becoming the YouTube of data? It seems to be on the way there.

The crucial factor that distinguishes the YouTube from the NotYouTube is the network effect. The genuine YouTube is the default, the unquestioned center stage. An also-ran may have faster servers, nicer staff, and more permissive rules, but it’s still not YouTube. With volume like this, Tableau Public is well on its way to becoming a true YouTube.

In the meantime, there seems to be another reason for satisfaction at Tableau Software. Elissa asserts “plenty of evidence” that new, purchased licenses for Tableau Desktop and Tableau Server are coming in that started with awareness of Tableau Public.

Wipe away that tear you have shed for BI marketing. Take heart in this: The golden oldies — those tired verses like “faster, better decisions” — have never come closer to receding into the support roles where they belong. A new strategy has been proving itself able to hook even onlookers who swore they really didn’t give a damn.

In the most recent example, a simple Tableau Public-hosted chart on Wired caught me looking. And thinking. It hooked me with a bar chart that compared rates that iPad users pay for downloading data.

Did I say that I really don’t care what iPad users pay per gigabyte?

I looked. There’s the U.S., I thought when I saw it, losing again. I’m used to that by now. But who’s losing worse? Belgium! Why Belgium? I thought of reasons, but none seemed to explain why a gigabyte there was more expensive than a gigabyte in Italy, another country I know a little bit about. Better price supports for waffles than for cannoli? My local Belgian thinks she knows the reason: “Taxes!,” she says. But I told her that that explains nothing at all, and that conversation continues even today.

Sure, it’s all a lot of fun. It’s powerful, too. The simple chart that can hook you on the fly — by making you notice, making you scratch your head, making you try out one angle after another in the quiet of your moment’s pause — can hook customers with modest budgets and legions of casual users to excite.

Our Department of Unwanted Customers has heard from Don Farber of KnowledgeSync about an inquiry from the Strategic Air Command.

As you may know, the KnowledgeSync tool monitors activity and generates alerts. Event A occurs and, bang, an alert flies off by email, text, perhaps even ICBM. New sales inquiry? The tool can even issue a reply.

What could SAC want to do with such automatic alerts? Don, who is VP of sales and marketing, recalls saying to his boss, “‘You can take this customer if you want to, but do you really want to take that support call?’” Nope.

He and I went on to fondly recall those two 1962 films, “Dr. Strangelove” and “Failsafe.”

A friend of mine runs the library at a small university near me, and she hears pitches all the time for neat technology. I suppose she doesn’t hear much about BI, just library stuff, but let’s not get hung up on the details.

To keep her priorities straight, she keeps a “ruthless focus” on the library’s real needs. She keeps Maslow’s hierarchy of needs in mind, the theory that people satisfy needs in order, from basic needs like breathing all the way up to “self actualization.”

She tells about one upstate New York librarian she heard about back when libraries were first urged to go online.

A consultant went to visit a small library — one of those Barbie Dream libraries that are hot in the summer, cold in the winter, and staffed so minimally that the library worker covering the single desk will excuse herself to change the toilet paper and greet the UPS delivery person.

So the consultant explained to the library director that the online catalog could do this, and it could do that, and it would have all these marvelous functions, and the library would be so much farther ahead, etc. etc.

And the practical old librarian who had been quietly listening tilted her head and replied, “I’d still rather have a flush toilet.”

I hear so much about “solutions” that I think are probably not solutions at all. So I found K.G’s excellent post refreshing. See what you think.

To get a data architect I know worked up, just ask him about how customers end up buying the wrong tools.

How about sales people who push federation tools on those who actually need data warehouses?

“It all sounds extremely sexy,” says my source, who works for a major business intelligence vendor and whom I can’t identify. “You have a lot of people who exaggerate their ability to combine data to provide business solutions. … They don’t prototype, they don’t profile, they don’t actually think about the problem or do testing or even send some high school data analyst out with Excel to put something together that [the customer] might want. They don’t do that.”

Many sales people tout EII because that’s what they have to sell, he says. “The EII tools give you your data, warts and all,” he says. It’ll work fine as a data warehouse substitute “if the data’s pretty clean to start with, if it has a somewhat similar structure, if you can define the data you need, if the data’s relatively common across all the sources, and if there’s not much duplication.”

Even if the salesperson has a more appropriate tool than what the customer asks for, the customer may never hear about it. “‘Fine!,’” thinks the salesperson. “‘If you want to buy a hammer, that’s fine. If you want to buy a wrench, that’s fine. It’s not like I care. It’s just sales to me.’”

Just once, says my source, he’d like to hear one of these questions: “How long does it take for a novice to become OK at this task?” Or, “How long would it take for an expert to become proficient at these two things?” Or, “If I have a failure, what is your tool’s usual process for recovery, and what gives your tool more integrity than others?”

Mark Madsen, meanwhile, has been been thinking about similar problems but from a different perspective. He’s research director at the Third Nature consultancy and a keynote speaker at this month’s TDWI conference in Las Vegas.

One source of problems he sees is vendor marketing. “It’s all about ‘our tool does this’ or ‘has these features,’” he writes in email. “A lot of people don’t think about them that way. They think about them as ‘what this tool is for.’” People end up using an ETL tool for real-time synchronization, for example, or a federation tool in place of a data warehouse.

Even product documentation can lead users down dark paths. “All those docs that say what the features are help when you know what feature you want,” he writes. “When you’re trying to accomplish a task, you’re thinking in a different way.” A common result: convoluted solutions.

“I once did something in an ETL tool,” he writes, “and the product developer said, ‘That’s not how you do that.’ They had built around an improper conception of how users apply it.”

Design schools tell you that every user has a theory of how anything works, he writes, which determines their approach to it. Wrong theories explain why people push on doors that need to be pulled, for example. He says that this insight has made him change his approach to teaching his courses or showing clients.

“I’ve realized that I need to start with the ‘what this thing is for’ and move into what you do with it, and how it works.”

Mark may go into this more in his keynote at this month’s TDWI World Conference in Las Vegas. His long-running “Clues to the Future of Business Intelligence” — perhaps the “Cats” of tech presentations — has been one of the most interesting I’ve seen in any tech industry. I expect “Stop Paving the Cowpath” to be worthwhile.