Sabrina Kuhrn’s vast interest in math, science and engineering was formed in the later stages of high school and led her to pursue a bachelor’s and master’s in financial and actuarial mathematics from the Technical University of Vienna. She joined Bank Austria in 2013 during her studies and is now responsible for the development of statistical models for customer behavior analysis, her first output being an online pre-approved consumer loan brought to production in 2017, where the credit decision is based on the algorithms she developed. The overwhelming amount of data and her passion for optimization led her to advance her computational skills by taking software engineering classes at the Technical University of Vienna from 2017 onward. Her successful application to the Wolfram Summer School will enable Sabrina to expand her horizon of statistical methods to analyze, interpret and visualize data quickly and accurately.
Project: Automatic Data Visualization
Design heuristic rules to automatically visualize various types of data. The project would combine statistical analysis and unsupervised/clustering methods along with the wide variety of visualization techniques the Wolfram Language has to offer.
Main Results in Detail
“A picture is worth a thousand words.” While trying to obtain information from large volumes of data, it is useful to visualize it in a meaningful way. However, the greatest challenge is to find the appropriate tool to visualize the underlying data. In this project, we have explored the various kinds of data visualization tools the Wolfram Language offers and have come up with automatic rules to infer the data type and decide automatically the exact plot type to use for the data. As the Wolfram Data Repository offers a large amount of curated data, we used examples from there.
As large volumes of data imply a high number of visualization methods, there are way more informative visualization techniques that can be explored further.