Data Wrangling Bio

@Brought to you by Rmd and Rstudio

Introduction to Me!

Welcome! I’m Thuong Ho , Business Information Systems graduate passionate about data-driven decision making leveraging story telling with data and project management abilities. I have always been interested in healthcare policies and disparity. I have been doing some substance use disorder policy impact research for Kentucky the past 3 years and I would like to apply concepts I will learn from the MS-BANA to explore fraud analytics and policy improvement.

I am from Saigon and started my study abroad journey Northern Kentucky University in 2019. I love to travel and a big fan of different cuisine :D!

Academic Background

  • B.S in Business Information Systems (Northern Kentucky University)
  • M.S in Business Analytics (University of Cincinnaty) **In Progress

Professional Background

I am currently a Data Developer/Analyst at Great American Insurance Company . I am mainly responsible for Predictive Analytics scoring engine data engineering. My daily work includes:

  • Building automated ETL or ELT data pipelines
  • Design database modelling
  • Creating operational and profitability index reports
  • Developing procedure using Python to utilize LLM as a judge
  • Responding to any business or technical ad-hoc requests

Experience with R

I am a beginner in R. I have taken a Business Analytics class in undergraduate using R. Check out the multi-variate regression model we built using R to predict abalone age at abaloneMLR! Besides that, I used it at work for some data prep, profiling, and analysis.

Experience with other analytic software

I am most familiar with SQL which honestly is not an analytic software. Python feels more intuitive to me than any other languages as it mimics the object oriented programming concepts. I believe the foundation is important and once you learn one language you could easily switch to another, it is just a tool for you to complement your analysis. All it matters is your probability and math background to derive information from data. I learned some limited analysis in Excel, SAS and SPSS.

Function Code Chunks

Question 1: Compute \(100 \times \left(1 + \frac{0.05}{12}\right)^{24}\)

## [1] 110.4941

Question 2: What is the remainder when 3333 is divided by 222?

## [1] 3

Question 3: Investigate the behavior of \(\left(1 + \frac{1}{n}\right)^{n}\) for large, integer values in n. In this case I investigate when n equals 1, 10, 100, 1,000, 10,000, 100,000, 1,000,000, 10,000,000, 100,000,000, and 1,000,000,000.

##  [1] 2.000000 2.593742 2.704814 2.716924 2.718146 2.718268 2.718280 2.718282
##  [9] 2.718282 2.718282