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 (SAS Institute) 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.

This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.