Last week I was in Las Vegas to attend Tableau’s user conference, or as attendees call it, “TC19”. Full disclosure: I had never been to this event before, and I was genuinely not prepared for the experience. This was a seriously high energy group of people, hopped up on… wait for it… data!

Held at the Mandalay Bay, over 20k attendees – the vast majority of them millennials – witnessed several days of enthusiastic demonstrations of how the company’s technology makes sorting through data more interesting – and therefore more useful.

If you don’t know a lot about Tableau prior to their recent acquisition by Salesforce (as many people did not), here is the company’s story in a nutshell. Based in Seattle, it launched its first product 2004 – a self-service data visualization tool. By 2008, the company had extended the self-service part to be a full-service tool, and felt strong enough in its breadth and depth to start calling itself a “system.”

By 2010, Tableau had 100 employees. Last year it had 4,500. Whoa! If you take into consideration its recent acquisition by Salesforce, it’s now part of a nearly 50,000 person entity. So far, much of the company’s growth has been in replacing what it calls “traditional” BI systems like Cognos, Microstrategy and Business Objects. Clients include Charles Schwab and JP Morgan and in financial services, technologists like Netflix and Spotify, and retailers like Home Depot and REI.

Tableau sums its vision up in 7 words: “We help people see and understand data.” And from what I saw, they are laser focused on just that. And as I mentioned, very excited about the ways that they are doing it. The majority of the data visualizations I saw (or “vizzes,” as users call them) are designed to make data that has historically been thought of as boring much – much – more interesting to look at. And as a result, a lot more actionable.

But why so popular? These people are loud and proud data nerds (I saw some absolutely hilarious demonstrations of nerdery at this event, and several of them brought a legitimate smile to my face). Isn’t data supposed to be just for weirdos with a predilection for finding trends within chaos (like me, and Brian, and Paula…)?

According to CEO Adam Selipsky – no. Data is for everyone. In fact, Selipsky’s real push for his clients is for each become to its own “data culture”. This term lost me at first (with the term “democratization of data” having such a foothold already, why reinvent the wheel?), but as the content rolled on the picture started to fill itself in. Through a story he told about the female codebreakers who helped the Allied Forces win WWII, the CEO pointed out that the structure of data scientists overseeing power analysts overseeing business users, all in descending order of access and “need-to-know”, the architecture that was so successful 80 years ago is still largely in use today. And he believes it’s time to change that.

This data culture means that everyone has access to everything. Everything. One of the cooler example I saw involved Southwest Airlines. Mark Jewett, Tableau’s lead of product marketing, addressed how most leaders get really concerned the moment the concept of widesperead access to data comes up. “We believe that people feel accountable when they are trusted, so it’s our job to show what accountability looks like.” As a result, Southwest began a bold initiative to find out what this accountability and trust would look like, but in a not-so-scary way. When it introduced Tableau to its workforce, it did not start by providing Southwest’s sensitive data – it populated the system with harmless content that would hold workers’ interest: data about athletes competing in the Tour de France, information about reality TV (specifically: The Bachelor) – just to familiarize folks with the tool and its capabilities. The result? Before Southwest even populated the tool with enterprise information, it had grown its active pool of Tableau-proficient users from 3 people to 2900. Clever.

Demo after demo showed users deep in the trenches of a retail operation accessing data they would never, ever, have dreamed of having access to in the world I grew up in, but to Selipsky, it’s all part of a culture of inclusion (more on that in a moment). As of today, Tableau estimates that only 24% of enterprises have full access to all of their data. Worse yet, only 8% can achieve data agility at scale.

Will people accept such a drastic concept? Will retailers willingly offer sensitive and powerful data to everyone at all times? The company is betting that with some convincing, that’s exactly what they’ll do. And clearly someone agrees with them, because Salesforce just paid a rather handsome sum to complete its full acquisition of Tableau. In fact, at the time of the event, a UK-based embargo forbidding the two companies from openly talking with one another had only been lifted for 8 days, so the entire event had a feel of “no one really knows where this thing is heading, but we’re all pretty certain it’s in an exciting direction”.

With so much technical overlap (Salesforce’s Einstein AI engine is meant to make sense of data, after all), the initial question of “Did Marc Benioff buy these guys just to take them out of the picture?” loomed large at first. But the more I saw, the more convinced I became that this was not the case. It’s early days, and it will be a while before anyone knows exactly how Tableau-generated data will feed into Einstein predictive tools or how the process flow of creating those next best actions will look, but I saw enough to know that Salesforce will gain quite a bit from having Tableau’s analytics capabilities on board. This isn’t just the case of one socially-conscious company finding a great cultural fit in another, as much of the love story has thus far been spun (Both companies are extremely proud of the socially-conscious fabric sewn into everything they do, and Benioff at one point referred to to Tableau “as if we found our missing relative in the Pacific Northwest”). But make no mistake: there is much money to be made here.  

I’ll have more next week when I write up the Salesforce Dreamforce event, but safe to say: this is the beginning of a relationship between two parties who have both, independently, long been looking to give enterprises the ability to make better decisions – but one that is rooted in deep, deep appreciation for the power of data.