What’s the hardest part of training a new data analyst? Resetting the trainee’s mindset.

“They start out with the idea that there’s a right answer,” says Joe Mako.

Joe’s leaving his job — where about one year ago he began analyzing data — to go work for the producer of Lyza. Lyzasoft CEO Scott Davis sees him as a “prototype” of a kind of creative, resourceful analyst that Lyza was designed for. Joe will engage with other analysts to evangelize Lyza and to help new users ease into the flow.

Joe, 29 and a veteran of two Army tours in Iraq, started out on the help desk. He answered calls from within the company, an ISP. Many callers couldn’t or wouldn’t analyze their own data, so Joe did it for them. His boss also enlisted his help — and now won’t dare go without a backup.

The first people he’ll help get into the flow are the two women who’re replacing him, and he’s got to do before he starts at Lyzasoft on November 9. They’re some of only a few in the his group who applied. Most others refused the “boring” work with “ugly” data.

New users, he says, want to know, “Where’s my wizard?” There is none. “But that’s why I enjoy these tools.” He uses Lyza and Tableau primarily. “They stay out of my way. They enable me. It’s just me and the data. … That’s what’s neat. But [new users] don’t know where to start.”

“I’m handed crazy files without any structure,” he says. The first thing new users have to know is that, no matter how ugly the data may be, it really can be cleaned up. He demonstrated to his new trainees, he says, and “they were blown away.” After that, he started showing them how they can clean up data on their own.

He explained basic steps and functions. Then he showed them how to combine tools, such as how to use two functions in sequence. And deeper still.

“It takes time playing to figure out where you need to get to,” he says. “You have to just go and play. If one thing doesn’t work, you try something else.”

“I always thought that data was exact,” he says. “If not, it was garbage and I’d throw it out.” But he later learned that there’s usually only a portion that’s garbage — that somewhere within the crazy mess there’s a story. “Even if every data point is wrong, there still might be some trend you can see. If there’s a bunch of ugly data, how do you figure what he story is?” It takes a willingness to figure it out, to untangle it, to find out what’s in there.

That’s a skill, not a talent, he says. “I’ve watched [his two replacements] get it closer and closer, learning to merge other data in, to reshape it and finally produce the output.”

Closer and closer. Business will trudge ahead, training a Joe here and a Joe there until people don’t complain anymore about boring work with ugly data. Someday, many more people will welcome the chance to do this work.

Back in February when I heard about Lyza, I thought right away of Tableau. Despite each one’s different strengths in data discovery and analysis, each appeals to the same broad group.

It’s an old group that’s getting new attention: creative analysts, or “cowboy analysts” to some. The like their data raw, not aggregated. They ask questions, forage, synthesize, analyze, and publish.

Joe Mako is one of them. Tomorrow, he’s launching a website for people like himself who use both Tableau and Lyza. Makometrics will publish every Monday morning and sometimes more often.

Joe is a network engineer at a Midwest ISP. He started at the tech support desk, where he saw how much help people needed looking at their data. “They didn’t understand exploring data,” he says. “They just don’t care.” But Joe cared enough to help with data analysis, and pretty soon someone gave him a tag line: “Make it happen with Mako.”

Posts he’s lined up so far:

• He’ll walk through data analysis problems from challenge to resolution. “I’ll be practicing something akin to the cycle of visual analysis.” (See the Tableau video “The Zen of Visual Analysis.”)
• Analysis of strengths and weaknesses of Tableau and Lyza
• Analysis of his “Visualizing Rambo Kills”: how he approached the dataset, and how he created the final result.
• Demonstrate sophisticated techniques in Lyza and Tableau. He’ll go into detail on such things as combining Lyza’s “previous” and “if” functions and the basics of summary functions like “sumcolumn” and “avgcolumn.”

Check it tomorrow (Wednesday, July 1): makometrics.com.