It was nearing the end of Day One at Tableau Conference Europe, and she was inviting me to watch her Tips and Tricks session the following day.
"I'll be showing three different tips," she said. "You've probably seen them before."
"I don't know about that," I said. "There's lots of things I don't know how to do."
"Well, one of them I know you'll know already," she insisted. "But you've probably heard the other ones too."
Do you know the punchline already, dear readers?
Of course you do. I had never seen any of the three techniques that Mina Ozgen eventually demonstrated at the aforementioned session. Neither had I seen any of the tricks her co-presenter, Robbin Vernooij, showed. But this is Conference in a nutshell, isn't it? Learning things you didn't know before; learning how much less you know than you thought you once did; learning how different everyone's experiences are.
And, not for nothing, realizing how many of our assumptions are wrong--not only assumptions we have about others, but also assumptions others have about us.
Rewind to my first Tableau Conference: Austin, Texas, 2016, not two years ago. I was full of assumptions about things.
I assumed nobody would know me.
I assumed that I was pretty strong, technically, but could benefit from going to technical sessions if they were REALLY high level.
I assumed none of the big-name presenters would want to talk to me.
I assumed it would be a long and lonely week.
All of these were wrong, of course.
Speakers were universally pleasant and welcoming when I spoke with them after their talks. Some even knew who I was, which was crazy to me. I learned that the technical talks were interesting, but I would be better served by going to the talks with the best speakers--and you could use room size and session-repeats as a good proxy for measuring that. I was adopted fairly quickly by my local TUG leaders (even though I had yet to attend a single session), Cesar Picco and Brittany Fong, and introduced around as though I were their oldest friend.
I arrived at the conference feeling invisible and insecure, a small voice in the wind, expecting to float anonymously through an ocean of strangers. I left feeling seen, heard, respected, accepted.
I assumed I was nobody to anybody. But instead, I discovered, I was somebody to many.
I was second in line for the live Makeover Monday last Tuesday, behind only Daniel Caroli (who one would assume would have had other plans, given his impending Iron Viz competition), having arrived early so that I would not be shamed later by Mr. Kriebel and Ms. Murray, which would have been the inevitable result were I to have been locked out of the session (as had happened last fall in Las Vegas).
We sat in long narrow tables. As the Sweden-Switzerland Round of 16 match played on the screens, Andy encouraged us to introduce ourselves to our table mates before the session began.
"Hi, I'm Mike," I said, extending my hand across the table.
"Oh, I know who you are," he replied.
He knows who I am.
As it happens I also know who he is, not by sight but by name: Michal Mokwinski, a regular participant in Makeover Monday. Unfortunately, I also know who I am, and that person is this: a person who will not live up to expectations in a time-boxed visualization exercise. I hope I can find something interesting in this dataset that I can whip up and explain in--
Eighty-five minutes later, I was staring at a Tableau workbook with four half-constructed, meaningless worksheets, no dashboard, and no story. I had four or five Chrome tabs open to various pages, remnants of my fruitless fall down a rabbit hole, wherein I was trying to get an explanation for what looked like one anomalous data point in a recordset with thousands of rows.
Exposed! Exposed as a fraud, I was soon to be. I very quickly threw some data onto a single worksheet, annotated my outlier with "This data point is weird" and uploaded my file.
Lest you think I jest: this was my final workbook. Impressive, huh?
I proudly/sheepishly showed my final product to the other people at my table. I wonder if a few assumptions were shattered in that moment as well.
Later, I ran into Chris Love and Rob Radburn, the duo behind both Data Beats and the "Freak-alytics" talk (which will be a must-not-miss session for those of you attending this fall's New Orleans conference).
"Did you do the live Makeover?" asked Chris.
"I did," I replied.
"How did it go?"
"Well," I said, "I had to do it quickly, so it was terrible."
They laughed at this. It was the laughter of the kindred spirit, the laughter of men who consider themselves among the dedicated tortoises (<---stolen right from their talk), and not the hares. Like a good barbecue (not a grill, mind you, but a barbecue--contact Ryan Sleeper for more information about the distinction), a good data visualization--at least, the way I do it--requires a lot of time. It's a slow-cooker.
Now, not quite two years after my first conference experience, I'm attending the European conference as an American, blessed and burdened with the sobriquet of Zen Master. Gone, then, is the assumed anonymity; and arrived are a whole new set of assumptions.
Not my own assumptions, though.
Rather, it's assumptions about me -- that I would be possessed of a full complement of technical knowledge, that I would effortlessly generate beautiful insights before second-half stoppage time, that I was only deigning to attend because I had some presentation to give (which I did not).
No, no, no to all of those things. This two-day version of TC, this Conference Concentrate, was a chance to disregard the "Master" moniker, and instead to enjoy 48 hours as a Zen Student.
Obliged to do nothing but indulge my opportunities, I soaked up all kinds of knowledge from the absurdly talented Euro-based Tableau community; particularly, of course, the Data School graduates, about whom I cannot provide enough glowing praise. (And I am famously stingy with praise.)
I watched my fellow practitioners demonstrate their technical craft, their creative sides, their philosophical depths.
I wore Simon Beaumont's hat and Anya A'Hearn's pins.
I sat next to Neil Richards as he watched his childhood chess hero make a move against him in an online match.
I watched Jonathan Drummey produce an iPad from thin air and begin to explain complicated Tableau arcana to Emily Chen and Laura Peterson...in a bar...at 11pm.
It was all the joy of the U.S.-based conference, with the main difference being that it was lamentably shorter.
I ran into Mina again at the Data School booth, some time after her session was over. "You know," I told her, "I hadn't actually seen any of those tips before."
"Oh, really?" she said, surprised. "Not even the Grand Totals trick?"
"No," I replied, "and--not only had I not seen that one, but I've never even seen that LOOKUP filter trick that you sped through at the beginning, and I'm not even sure I know *why* it works."
"Oh, wow! Well, here," she said as she looked around for a laptop. "Let me show you."
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