Graduate student in Business Analytics at LMU, skilled in Python, SQL, R, Tableau and more. @OliverLin
As another part of the summer capstone project of my MSBA program, working with LAEDC, I created an Alteryx workflow that cleaned and appended data to the National Establishment Time Series (NETS) data on foreign direct investment (FDI). And I used the cleaned and enriched data to create this FDI Dashboard for LAEDC.
During the summer capstone project for my MSBA program, working with LAEDC, I collected the various ACS (American Community Survey) variables across 2011 to 2020 from the US Census Bureau and designed this dashboard. The target audience is foreign direct investors. And the dashboard is intended for foreign investor to get a better sense of California's local environment and inform their decision-making.
In this project, me and my group used various analytical techniques including natural language processing (NLP), BERT sentence embedding, K-means clustering to extract insights from Twitter on reMarkable to generate actionable insights for reMarkable, a Norwegian-based tablet company. We earned the opportunity to present our project to reMarkble's co-founder and VP of Marketing, who where very impressed with our project.
This project adopts the investment principle covered in Joel Greenblat's book The Little Book that Still Beats the Market. Using ROA and P/E ration to evaluate a company's performance and how it is priced, in order to identify undervalued stocks and inform investment decision making.
The objective of this case is to train a decision tree to predict if a individual's income would be above or below $50,000 based on some attributes about them such as their race, sex, education and work class etc. There are a total of 48842 records in this dataset.
In this project, we use dictionary based approach to create a Naive Bayes model to classify messages as either spam or non-spam messsage.
In this project, I collected data from redfin.com, cleaned the data with Excel and Power Query, and created visualizations using Tableau.
In this project, I simulated airport operation with Excel Data Table. Consider and compared various different expansion possibilities and offered recommandations based upon the analysis.
In this group project, we looked at movie statistics from the past 30 years, and found insight in factors that contributes to a higher box office. Upon which we created our own movie idea based on the most popular genre and keywords. (Team members: David, Johnathon, Justin, Kyle and Monami)
This group project features a analysis on crime statistics in LA and COVID-19 data in the past two years using ArcGIS Pro. (Team members: David, Johnathon, Justin, Kyle and Monami)
In this project, we conducted various analyses on a office supplu company. I specifically conducted survival analysis and created visualizations using R. (Team memeber: Megan, Alena and Aoun)
Los Angeles, CA