Data + Women: Lessons from a Promising Data Explorer

By Erin Stevens 08 Out, 2015

Note: This is the third installment of a four-part series highlighting our Data + Women panelists. The first two pieces highlighted humanitarian Jennifer Chan and Wells Fargo executive Christine Birtel. The panel will take place at this year's Tableau Conference.

Some people say they like math because the problem always has one right answer. But Tara Kats says she loves math because there can be more than one right answer.

Tara learned formulaic equations like the rest of us. But her perspective shifted while taking upper-division math classes in college.

“You get a starting point and a finishing point, and you fill in the gap,” she says. “It’s not, ‘Start here. Where do you end up?’ It’s, ‘Start here, end here. What’s the journey?’ And that was so much fun for me, because that’s where the creativity comes in.”

Tara’s Specialty: Deep Data Analysis

Tara found data analysis to be satisfying for the same reasons and joined Tableau right after college. She started as a data analyst on the Tableau Public team, helping journalists and bloggers tell stories with their data.

“Your job is to play with data and to teach people how to play with data,” she says, adding she especially enjoys going beyond what the data says to figure out why the data says what it says.

But during her second year on the job, she found herself wanting to dive even deeper. Last July, she took on a new role as a product marketing specialist to focus on what she calls “the really heavy stats stuff.”

“I really found that my passions were so ignited with statistics and analytics. More specifically, LOD Expressions really rang true to me,” she says.

Question: How to Get More Women to Gain Deep Knowledge of Data?

Just 20 months into her budding career, Tara has already learned some valuable lessons and made impressive progress. But she also has questions to ask. For instance, she says she sees quite a few women in leadership positions, but she suspects the numbers don’t tell the whole story.

“I’ve noticed that some of the higher-ups—the people who have tons of expertise in data—are men. And it would be nice if it were not such a stereotypical thing that’s so true,” she says. “But I’m not really sure what the path is to get there. I would love to talk about that with someone.”

Tara poses with her colleagues.

Lesson #1: Trust What You Know, and Ask What You Don’t

Tara says she doesn’t have a mentor per se, but various people have encouraged her to push herself and to have confidence.

“I’ve had people in different stages of my life who’ve told me: ‘Trust what you know, and what you don’t know—ask.’ I think that’s the best advice.”

She took that advice to heart while looking to start her career. She scheduled a series of informational interviews to learn more about her options, and to ask questions.

“What do you do day to day? What do you like about your job? What do you not like about your job? What do you recommend for me to do if I would ever like a job at this company? What types of entry-level jobs do you have at this company?” Tara says.

These conversations helped her not only define her own wants and needs but also land her first post-college job.

“Talking to people is one of the best advice that I was ever given,” she says.

Lesson #2: Seek Balance

When she first started her job at Tableau, Tara found herself completely immersed in her work—even when she when home. She soon realized she was thinking—and talking—about little else.

“And there came a point when my fiancé was like, ‘I love that you’re telling me all of this and I love that you’re excited about it. But also, there’s more to life than work.’ That’s the best thing anyone could’ve told me at that point, because it was true,” she says.

Tara has since learned to seek balance—to keep work at work, and home at home.

Lesson #3: Keep an Open Mind and Learn from Other Data Explorers

Tara says she’s much too young to give anyone advice—“I feel like I have to have my own voice before I can tell someone else what voice to have,” she says.

But that’s the beauty of data exploration, says Tara. In coaching an intern on her team, Tara’s main message has been to explore the possibilities.

“I’ve tried to show her how to think about things, and tell her that, ‘Hey, just because I‘m thinking about it this way doesn’t mean that it’s the right way or the only way,’” she says.

That’s what she loves about data. It's just like math, says Tara.

“It’s not like I’m telling you this is how it has to go,” she says. “Data analysis, in my mind, is really a collaborative field, and everyone has something to learn from everyone else because we all think about it differently. There’s no set box that it’s in, which I love.”

Coming to this year’s Tableau Conference in Las Vegas? Meet our Data + Women panelists and join the conversation at our meetup on Monday, October 19. You can also share your thoughts on our Data + Women Community Forum.


Submitted by cem kaptanoglu (não verificado) on

We need some example of pure mathematics notification of yours deep data analysis.