Introduction

I grew up in Columbus, OH, and came to Cincinnati in order to attend the IT program at UC. I’ve was a student worker for Campus Services IT throughout my undergrad program, and was hired on full time after graduation.

Me and the dog
Me and the dog

Academic Background

education <- data.frame(
  College = c("University of Cincinnati"),
  Degree = c("BS in Information Technology",
              "Masters of Business Administration",
              "Masters Certificate in AI"),
  Complete = c(TRUE, FALSE, FALSE)
)

library(knitr)
knitr::kable(education, caption="Education")
Education
College Degree Complete
University of Cincinnati BS in Information Technology TRUE
University of Cincinnati Masters of Business Administration FALSE
University of Cincinnati Masters Certificate in AI FALSE

Professional Background

Full Time Employee

Co-op Positions

  • Seapine Software (Quality Assurance)
  • Management Systems (Java Developer)
  • ADgility (Web Developer)

Experience

R

This class is my first exposure to R. I have explored data analytics tools before, so I had an awareness of it’s existence. However, given my programming background I always fell back to python tool sets instead.

Other Analytics Software

My data analytics experience has been limited to basic Excel tools. Expanding the definition of “data analytics” I do have experience with the following reporting tools and databases:

Reporting Frameworks

  • Crystal Reports
  • BIRT

Databases

  • Microsoft SQL
  • Oracle
  • MySql
  • Postgresql
  • SQLLite
  • Sybase
  • MongoDB
  • … probably a few more I can’t remember

Programming languages I have used to analyze data

  • Python
  • Ruby
  • Powershell
  • GoLang