Date of Graduation
5-2023
Document Type
Thesis
Degree Name
Bachelor of Science in Industrial Engineering
Degree Level
Undergraduate
Department
Industrial Engineering
Advisor/Mentor
Rainwater, Chase E.
Committee Member/Reader
Kent, John L.
Abstract
In modern society, technological capabilities and the amount of data readily available to users continue to grow exponentially. Many have adopted these new capabilities but lack the infrastructure needed to efficiently utilize high-powered software and programs. Without a method to collect, store, and process large datasets in real-time, individuals and businesses can quickly become overwhelmed, inhibiting effective decision-making processes. There is potential to improve decision-making abilities by enhancing the computing infrastructure. To accomplish this task, we will explore the ideas surrounding High Performance Computing (HPC) and data visualization software. High Performance Computing is the ability to process data and perform complex calculations at high speeds by using a cluster of computer servers that work in parallel to boost computer power. This research will seek to expand on the benefits of joining HPC systems with data visualization software such as Power BI. The Arkansas High Performance Computing Center (AHPCC) will be used to demonstrate data processing capabilities, and Power BI will be used to translate the data into effective decision-making visuals. While this project focuses on a small test scenario, the results from this research serve as motivation to implement this type of visualization pipeline in a variety of industries to help key stakeholders better analyze the state of businesses in a real-time environment.
Keywords
Risk analysis; risk management system; visualization pipeline
Citation
Joslin, P. (2023). Automated Visualization Pipeline for Near Real-time Risk Management System. Industrial Engineering Undergraduate Honors Theses Retrieved from https://scholarworks.uark.edu/ineguht/88