For each prospective client engagement, Micronotes employs its Digital Prescreen Acquire process to deliver a comprehensive market breakdown. Previously, this process, being semi-manual, consumed more than a day. Following the successful implementation of this project, the entire procedure is now fully automated, featuring a functional front end and promptly delivered results via email, reducing the time frame to 1-2 hours. Integral to this process is the utilization of anonymous ADS data, necessitating the development of a machine learning algorithm to ensure accurate record matching across different weeks. The successful completion of this initiative has not only enhanced the daily operational efficiency but also established a robust foundation for further advancements in the model.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Curley, Griffin
• Goings, William
• McCormick, Mirandi

Subject

• Learning
• Computing
• Industry
• Innovation
• Project-Based Learning

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-121523-090151
• 115254

Keyword

• Machine Learning
• Geospacial Zip Code Analysis
• Data Matching
• Azure Databricks
• Big Data
• Process Automation

Advisor

• Ryan, Jim
• Blais, Marcel Y.
• Sarnie, Robert
• Wong, Wilson
• Danke, Manasi

Year

• 2023

Sponsor

• Micronotes

UN Sustainable Development Goals

• Not Specified

Date created

• 2023-12-15

Resource type

• Major Qualifying Project

Major

• Mathematical Sciences
• Management Information Systems
• Computer Science

Source

• E-project-121523-090151

Rights statement

• In Copyright

Last modified

• 2024-02-07