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SmartData Collective > Uncategorized > No wizard, just you and the data
Uncategorized

No wizard, just you and the data

TedCuzzillo
TedCuzzillo
6 Min Read
No wizard, just you and the data
Illustration generated with FLUX.2 [klein 4B] via Cloudflare Workers AI.
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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.

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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.

Helping the two women who’re replacing him ease into their new jobs is just what Joe’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 while most others were repulsed by the “boring” work with “ugly” data.

New users want to know, “Where’s my wizard?” he says. “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 they have to know is that, no matter how ugly the data may be, it can be cleaned up. He demonstrated to his new trainees, he says, and “they were blown away.” Then he started walking them through.

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 found that usually there’s only a portion that’s garbage — that somewhere within the crazy mess there’s a story. “Even if every data point is wrong, there’s still 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, most people will welcome the chance.

TAGGED:data quality
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