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Data Meets Art 2025-11-20 · 14:22
Nathalie Miebach – data artist and Artist-in-Residence @ School of Data Science, University of Virginia , Alex Gates – Assistant Professor of Data Science @ University of Virginia

Here we explore the intersections of data, art, and storytelling. Our guest, Nathalie Miebach, is an internationally-recognized data artist and the School of Data Science’s inaugural Artist-in-Residence.

Using materials like reed and paper, she transforms complex datasets into woven sculptures and musical scores, inviting us to view and even hear data in new ways. Joining her is Alex Gates, assistant professor of data science at the University of Virginia research examines how patterns of connection shape creativity, innovation, and discovery.

Together, they discuss what happens when data meets art.

Chapters (00:00:01) - Data Points: When Art Meets Science(00:00:46) - Ian and Nicole: Introduction(00:06:18) - How Stories Get Made(00:09:59) - Basket Weaving Visualizing Data(00:20:33) - Wonders of the World(00:25:47) - Data and Artist Residency(00:27:50) - Breaking Habits in Creativity(00:30:06) - What is Data Science: Craftsmanship?(00:34:50) - How Art Affects Our Understanding of Data

Data Science
UVA Data Points

Sales forecasting and demand planning are critical business processes, but most organizations still rely on spreadsheets—leading to version control issues, fragmented approvals, and lack of historical tracking. Traditional BI tools struggle to solve these problems because they don’t allow for cell-level edits, inline comments, and structured approval workflows in a governed way.

In this session, Ian Reed will demonstrate how to:

Enable real-time forecasting by replacing manual spreadsheets with a structured, cloud-based data app Allow for cell-level edits and inline commentary so teams can capture assumptions behind forecast changes Implement an automated approval workflow with proper governance Integrate seamlessly with live data sources for continuous updates and visibility into actual vs. forecasted performance Track historical changes and maintain audit trails of all modifications

With Sigma, demand planning is no longer a fragmented, error-prone process—it’s a seamless, governed workflow that scales with business growth. Join this session for a demo and a step-by-step walkthrough of how this app was built, proving that anyone can create a highly customizable, enterprise-grade demand planning system in Sigma without deep technical expertise.

➡️ Learn more about Data Apps: https://www.sigmacomputing.com/product/data-applications?utm_source=youtube&utm_medium=organic&utm_campaign=data_apps_conference&utm_content=pp_data_apps


➡️ Sign up for your free trial: https://www.sigmacomputing.com/go/free-trial?utm_source=youtube&utm_medium=video&utm_campaign=free_trial&utm_content=free_trial

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AI/ML BI Cloud Computing Git Python
Sigma Data Apps Conference 2025
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