Heading to Las Vegas earlier this week for Tableau Conference 2015, several questions were rattling around in my brain. Perhaps the most talked about vendor in the analytics/BI space, Tableau’s stated mission is to “help people see and understand their data.”
Tableau is typically known as a provider of interactive data visualization software with a loyal, bordering on cult-like, customer base. So this naturally got me thinking – who are these “people” and do I have the intellectual horsepower to be one of them? Do you need to be smarter than me to use Tableau?
Now…let’s be clear about one thing right up front: My intelligence is questionable. I am not an early adopter of technology. I figured a snowflake schema was an operational initiative for northeast ski resorts. I could have been convinced that Apache Hadoop was a military outpost during the French-Indian war. I willingly watch The Real Housewives of New Jersey. The bar for being smarter than me is pretty low.
I do, however, have a graduate education in entrepreneurial business, and I helped build a seven-figure company from scratch in a hyper-competitive consumer space. Here’s why I mention this: I think there are a lot of people out there in the enterprise world just like me – people that wear several hats, and have a modicum of technology fluency and a strong appreciation for its proper use, but a loyalty toward business execution, above all else. In other words, data exploration and discovery is not explicitly part of their job description.
More on this in a moment, but back to the conference. I had heard about the vibe and energy from prior shows, but still wasn’t quite prepared for the prospect of 10,000 screaming data jockeys boisterously applauding each product announcement. Two things to note about these people, having met several of them: They are fiercely loyal to Tableau, and are incredibly talented in the art and science of data manipulation.
Tableau affectionately refers to them as “Data Rock Stars,” and rock stars they are. In 10 minutes, one of these warriors could spin up a visualization of my Netflix viewing habits superimposed with my Amazon purchase history. With that, they can then predict, to the penny, how much money I will squander in November on non-essential, post-ironic, pop culture garments (I already have the Los Pollos Hermanos and Underwood 2016 T-Shirts, so who knows where my adventures in frivolous spending will take me next).
From muted cheer to raucous ovation, these Data Rock Stars offered their reaction to an array of product updates and areas of investment, including:
- Data: Focused largely on Excel activity, the new capabilities include better scraping, cleansing, joining, etc. Most would fall under the now popularized concept of data preparation.
- Visualization: Greater interactivity, new shiny object – “viz within a viz” technology, upgraded mapping and geospatial capabilities.
- Analytics: Seemingly used interchangeably with “advanced analytics,” the stated goal here is to make advanced, predictive, and prescriptive capabilities more accessible to more user types.
- Self-service: A lot of discussion around IT activities to help govern and support scalable analytics at the enterprise level – includes enhanced dashboards and authoring capabilities.
- Mobile: Includes improved tablet interactivity, but also a new native Tableau app delivered to the phone. The biggest announcement here, however, was Vizable, a free mobile app optimized for tablet devices. Not requiring any existing Tableau ecosystem, this product is touted as providing greater ability to explore data and create reports and visualizations directly on the tablet itself.
At the risk of a grotesque oversimplification, I like to think about analytics through two different lenses: consumers and creators (often called authors). Consumers are served up reports and dashboards created by someone else. Their ability to drill down to detail, make updates, and further explore the data-behind-the-data depends on the tool in use, but also on the willingness and appetite of the user.
Creators, on the other hand, are the ones that really get their hands dirty with the data. They have the ability to connect and incorporate new data sources, create visualizations from scratch, and customize views of data to the audience at hand. This is the domain of the Data Rock Star.
In my view, most of the product announcements were geared toward the creators/authors of the world, and rightly so. This user persona is Tableau’s bread and butter. These are the people that create stunning, compelling, and thought-provoking visualizations to get people thinking differently about their business. There is an important distinction here, however. From what I can tell, the vast majority of these Rock Stars / creators / authors have job roles that are largely or exclusively focused on these very activities. In other words, it’s their job to do this stuff.
For throngs of other people in a line-of-business role, however, achieving this level of engagement and analytical creativity is much more difficult. When someone is behind on their quota, dealing with an operational fire drill, or racing to close the books at the end of a quarter, analytical creativity takes a backseat to the core job activities, and even the most data-curious business users slip into pure consumer mode.
So this brings us back to the initial question – do you have to be smarter than me to use Tableau, or more pointedly – am I smart enough to use Tableau? It depends. Of course it depends – it always depends.
As a consumer? Absolutely. The authoring, publishing, and sharing capabilities in Tableau online and Tableau server seem intuitive and approachable, and provide a clear pathway for people like me to get the answers that I need. Ditto for the attractive and seemingly versatile mobile capabilities displayed.
As a creator? I’m not entirely convinced. I’m no Data Rock Star and I never will be, but I do have a healthy appetite for insight and a genuine curiosity for what makes businesses tick. My problem, and I don’t think I’m alone, is that my discovery process is very fragile. As I’m seeking an answer to a business question and exploring data, the minute something doesn’t work the way I need or expect, I’m stuck. I can go running to IT or tap my local data artisan for help, but either way, my process is disrupted.
In fairness, I don’t know that any vendor has truly solved this issue of analytical fragility in the line-of-business. In my mind, the wildcard for Tableau is Vizable. Offered for free, this seems to be a “pusher”-type strategy to rope in more analytically inclined business users, slowly increase their comfort level with the process of creationism, and grow their own new and evolved species of Data Rock Stars.
Time will tell if this approach will work, but I and the rest of my flock will be watching, possibly with an insufferable Bravo network show playing in the background.