Description
In the age of information, collecting and processing large amounts of data is an integral part of running a business. From training artificial intelligence to driving decision making, the applications of data are far-reaching. However, it is difficult to process many types of data; namely, unstructured data. Unstructured data is “information that either does not have a predefined data model or is not organized in a pre-defined manner” (Balducci & Marinova 2018). Such data are difficult to put into spreadsheets and relational databases due to their lack of numeric values and often come in the form of text fields written by the consumers (Wolff, R. 2020). The goal of this project is to help in the development of a machine learning model to aid CommonSpirit Health and ServiceNow, hence why this approach using unstructured data was selected. This paper provides a general overview of the process of unstructured data management and explores some existing implementations and their efficacy. It will then discuss our approach to converting unstructured cases into usable data that were used to develop an artificial intelligence model which is estimated to be worth $400,000 and save CommonSpirit Health $1,200,000 in organizational impact.
Details
Title
- An Introduction to Unstructured Case Management
Contributors
- Bergsagel, Matteo (Author)
- De Waard, Jan (Co-author)
- Chavez-Echeagaray, Maria Elena (Thesis director)
- Burns, Christopher (Committee member)
- Barrett, The Honors College (Contributor)
- School of Mathematical and Statistical Sciences (Contributor)
- Computer Science and Engineering Program (Contributor)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2022-05
Resource Type
Collections this item is in