BigQuery Data Exploration Project

SQL Usage for Homelessness

Full, Organized Dataset

In this project, using BigQuery's dataset, I explored homelessness from 2010 - 2018 to draw insights into trends. Steps were taken to modify the dataset using SQL, allowing for more efficient analysis, including removing columns and creating new columns. Then, I performed data analysis using SQL queries to identify locations that need support for homeless youth and homeless veterans, in addition to sourcing locations that were effectively supporting their homeless population. This made it possible to understand where more help was needed and how to best provide it.

Deloitte Australia Data Analysis

Machine Stats for Company #1

Equality Fairness for Company #2

During the data analysis for Deloitte Australia, I completed a job simulation involving data analysis and forensic technology. Deloitte works with other companies to better help their systems and drive data-decision making. First, I began by organizing my information, then reviewing the asked queries. We wanted to learn about device systems and their statuses for this company's factories. I created two sheets, one to show the down time per factory and another to show down time per device type (1st photo shown above). Then I created a dashboard using Tableau to put the bar charts together. This provided data to the owners regarding their machines, so they were better able to decide next steps.

A second company's data was provided to help find out more information on salary equity between genders. Following the same steps as above, I then used Excel to classify the data and help draw business conclusions based on my findings.

Healthcare Costs: Insights into U.S. Medical Charges

Costs per Region

Costs per BMI Group

Costs per Age Group

Costs per Non/Smoker Group

Tableau Dashboard for All Previous Titles

For my final big project, I wanted to implement a health dataset. After tons of research to find a source file, I found Health Insurance Data, on Kaggle. I proceeded to complete the healthcare analytics project using the dataset to explore the factors influencing individual medical insurance charges. This project highlights my proficiency in Excel, SQL, and Tableau across the entire data analysis process. I began by cleaning the dataset in Excel—removing duplicates, checking for missing values, and standardizing categorical fields. Using SQL, I performed exploratory data analysis to compare average charges by smoking status, region, age group, and BMI levels. I identified key trends, such as significantly higher charges for smokers and increasing costs with age and BMI. Finally, I used Tableau to create a clear and interactive dashboard that visualized these insights, including bar charts, scatter plots, and regional comparisons. This project demonstrates my ability to prepare, analyze, and visualize real-world healthcare data while delivering insights that could support data-driven decision-making in medical and insurance contexts.

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