So many people who should know better seem to miss the point when they mention Tableau. Why? I asked BI veteran Stephen McDaniel for his thoughts — which he gave, but then went on to suggest an almost unheard of challenge: a data analysis face-off among vendors.
Consider this lazy description from a BI analyst: “Tableau provides business analysts speed of thought visual analysis on data held in memory on their desktop machines.” All that’s fine, but it may as well have been about a whole bunch of other tools, too.
At the root of this fuzz, explained McDaniel, is that most analysts who concern themselves with tools don’t actually use the tools. They rely on demos , marketing, and hearsay.
Though much of McDaniel’s recent work has centered on Tableau — his second book is Rapid Graphs with Tableau Software and he gives training sessions around the country — he also has a long, credible trail back through BI and data mining. He was director of analytics at Netflix, and has worked with more than 50 companies in BI. His first book was SAS for Dummies.
“I love SAS,” he says. Still, he remembers his sister in law’s reaction to his book on SAS. She was not an analyst but a “people manager.” These are the ones, he says, who have hated BI because “it had been made into a priesthood.” When she had looked through the book, she said, “Oh, this is great” and put it down. But she read the Tableau book for a half hour and said, “You should come talk to some people I work with.” She had recognized what she could do with the tool.
McDaniel’s sister in law and many like her don’t care whether the data is “in memory,” they don’t see themselves as business analysts, they take “desktop” for granted, and they know “speed of thought” is just gloss.
The list of features really doesn’t matter. All that really matters is whether someone can do what needs to be done with the tool.
McDaniel imagines a throw down, a data analysis match. It would be open to any BI vendor. Each vendor would send their best people, and each team would receive a uniform set of data. Over the some defined period, teams would analyze and then present the results to a panel of vendor-neutral judges.
The reward? Perhaps a signed copy of a Stephen McDaniel book, or maybe a beer, possibly both. But certainly, repute.
What do you think of the face-off idea? Please write a comment.
