Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA
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Bringing data to life: Combining machine learning and art to tell a data story

Nancy Rausch (SAS)
4:40pm5:20pm Thursday, March 28, 2019
Case studies
Location: 2007
Average rating: ****.
(4.80, 5 ratings)

Who is this presentation for?

  • Data scientists, city planners, executives, corporate event planners, communication specialists, marketing specialists, usability designers, web designers, graphic designers, machine learning specialists, IT specialists, customer relationship management specialists, and artists



Prerequisite knowledge

  • Basic knowledge of machine learning

What you'll learn

  • Explore interesting visualization techniques
  • Learn how to build a project through all phases of the analytical lifecycle, how to build a bot, how to build a predictive algorithm for solar array data, and how to process big data in a succinct way
  • Understand how to use SAS for analyzing data and streaming data techniques


Analytics and AI are powerful methods for extracting insights hidden in data. However, these methods by themselves cannot convey insights. Visualization is a key requirement for explaining analytical findings, but visualizations such as graphs and charts are not always enough to explain data, especially to a nontechnical audience. This audience may need a different approach to connect with the data.

Nancy Rausch shares a case study for a project that combined machine learning and art to tell a big data story. She explains how she and her team collected and prepared IoT streaming data from a solar array farm, applied an analytical model to forecast future output, and then visualized the results for general audiences using interactive art. They also used artificial intelligence and natural language processing to allow visitors to interact with the art installation. The project brought solar array technology to life in a way that was able to engage and delight visitors of all ages and backgrounds.

Photo of Nancy Rausch

Nancy Rausch


Nancy Rausch is a senior manager at SAS. Nancy has been involved for many years in the design and development of SAS’s data warehouse and data management products, working closely with customers and authoring a number of papers on SAS data management products and best practice design principals for data management solutions. She holds an MS in computer engineering from Duke University, where she specialized in statistical signal processing, and a BS in electrical engineering from Michigan Technological University. She has recently returned to college and is pursuing an MS in analytics from Capella University.