Using A Data Warehouse To Analyze Information About Insurance Claims And Policies

Jeff Rubillo

School Name

South Carolina Governor's School for Science and Mathematics

Grade Level

12th Grade

Presentation Topic

Consumer Science

Presentation Type

Mentored

Mentor

Mentor: Jim Stritzinger, IT-oLogy

Abstract

Big companies involving insurance, social media, and retail amass large amounts of data from day to day. Every time a user enters information about their profile on social media or about the order they would like to place, these data must go somewhere to be processed. These are stored in large databases, or data warehouses, that hold information about each person or entry. With these data, it is possible to generate significant reports which would benefit the company and assist in making informed business decisions. On the front end, most people are not aware of the potential these data possess. The back end process of examining data can significantly impact profits and reduce financial risks. The goal of this experiment was to discover if management reports could be generated from Seibel’s insurance data warehouse, which was accomplished after an analysis of their warehouses.

Start Date

4-11-2015 9:45 AM

End Date

4-11-2015 10:00 AM

COinS
 
Apr 11th, 9:45 AM Apr 11th, 10:00 AM

Using A Data Warehouse To Analyze Information About Insurance Claims And Policies

Big companies involving insurance, social media, and retail amass large amounts of data from day to day. Every time a user enters information about their profile on social media or about the order they would like to place, these data must go somewhere to be processed. These are stored in large databases, or data warehouses, that hold information about each person or entry. With these data, it is possible to generate significant reports which would benefit the company and assist in making informed business decisions. On the front end, most people are not aware of the potential these data possess. The back end process of examining data can significantly impact profits and reduce financial risks. The goal of this experiment was to discover if management reports could be generated from Seibel’s insurance data warehouse, which was accomplished after an analysis of their warehouses.