Webinar sob demanda

BI Trend #2: Liberal arts impact

Keeping up with the rapid pace of change in the BI ecosystem gets more challenging every year. With that in mind, we've put together a series of webinars focused on the Top 10 BI Trends in 2018.

In this webinar, we'll explore the growing influence of liberal arts in data analysis.

As analytics evolves, the focus has shifted from simply delivering the data to crafting data-driven stories that inevitably lead to decisions. And a liberal arts perspective can improve the way your organization makes use of data– one major insight at a time.

From more effective data-storytelling, to tackling challenges from different perspectives, the science of data analysis combined with a liberal arts perspective is becoming more helpful than ever.

Watch this webinar to learn how:

  • liberal arts is influencing data visualization and vice versa
  • you can benefit from data storytelling roles within your organization
  • to attract the right talent to help tell your data stories and uncover more insights

Check out the rest of the 2018 Top 10 Business Intelligence Trends webinar series.

Sobre os palestrantes

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Ben Jones

Director of Global Outreach Programs, Tableau

Ben is a mechanical engineering (UCLA, 2000) and business, entrepreneurship (California Lutheran University, 2011) graduate working for Tableau Software directing the Tableau Public and Academic Programs teams. HE is also the author of Communicating Data With Tableau (O’Reilly, 2014) and teaches data visualization theory at the University of Washington’s Professional and Continuing Education department. He blogs about data visualization at dataremixed.com and you can find him on Twitter @DataRemixed.

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Michael Correll

Research Scientist, Tableau

Michael is a research scientist with a background in visualization. His focus areas are statistical communication, graphical perception, and text analytics. He is interested in how visualizations can be used to persuade, and how to make audiences mindful of biases and uncertainty in their data. He is also active in the digital humanities community, where he looks at how we can create visualizations of text data that allow complex statistical modeling but are also easy to explain to audiences without backgrounds in statistics. Prior to Tableau, Michael was a post-doctoral researcher at the University of Washington, where he worked with Jeffrey Heer investigating how well people can estimate aggregate statistics from visualizations.

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