The project goal is to analyze and determine how the city's financial resources are distributed and how much of the budget is spent on overtime.

We utilized Google Big Query to conduct Data cleaning, Modeling (ML linear regression), and Data Visualization on NYU Payroll dataset. We explored this dataset by being in the roles of a job seeker and an NYC citizen. By being the job seeker, we have uncovered the salary and OT time trend in New York over the year of 2014-2020, and seen the top locations, top job titles and top tenures with the highest earnings. And by being the NYC citizen, we have researched on the allocation of NYC budget over different agencies and locations, with percentage change of budget spending each year. Furthermore, we have incorporated machine learning in our dataset using tenure, regular work hours, OT hours and locations to predict gross salary. For data visualization, we used Tableau Online and Tableau Public to visualize our data analytics research with dashboards and story.

Data source: https://data.cityofnewyork.us/City-Government/Citywide-Payroll-Data-Fiscal-Year-/k397-673e