Nashville City Cemetery Analysis 

- Excel

This project involves analyzing a dataset of burials in Nashville City Cemetery from 1846 to 1979, focusing on identifying trends in causes of death, burial demographics, and historical patterns. The analysis, which includes data cleaning, pivot tables, and visualizations, aims to compare Nashville City Cemetery with other historic cemeteries and create engaging marketing materials based on the findings.

Central Park Squirrels 

- Excel & Power BI

This Excel project focuses on analyzing squirrel behavior and characteristics, particularly those in and around a specific area in Central Park, NYC, using sensory data such as color, behavior, and response to humans. The analysis includes identifying squirrels near a baseball field, assessing threat communication behaviors, and distinguishing those not primarily colored gray, using formulas, filters, and additional data columns for detailed insights in this adorable project.

Budget Analysis

- Excel

This project was designed to enhance proficiency in Excel through focusing on formula creation, error handling, and data lookup techniques. We practiced calculating financial differences, utilizing advanced functions like VLOOKUP, XLOOKUP, and INDEX + MATCH for two-way lookups, creating dropdown menus with data validation, and visually representing data, aiming to master spreadsheet manipulation and data analysis skills.

App Trader Analysis 

- SQL

This project involves analyzing data from the Apple App Store and Android Play Store to advise a new company, App Trader, on the strategic acquisition of app rights. The analysis will focus on determining optimal price ranges, genres, and content ratings for acquisition targets, and will culminate in a Top 10 list of recommended apps for purchase, using PostgreSQL for data analysis and Excel for chart creation.

Lahmans Baseball Analysis 

- SQL

This project involves querying the Lahman Baseball Database, a 23-table relational database, to explore a wide range of baseball statistics and historical data, from player performances and team records to salary trends and game attendance. It addresses both specific inquiries and broader open-ended questions about the nuances of baseball's past and present.

Prescribers Analysis 

- SQL

This project involves complex SQL queries on an eight-table relational database to analyze prescription patterns, drug costs, and healthcare provider activities. The focus is on identifying prescribers with the highest number of claims, specialties with significant opioid prescriptions, drug cost analysis, and detailed examination of pain management specialists in Nashville, employing advanced SQL functions like window functions for comprehensive data analysis.

NY Airbnb Analysis 

- Tableau

This Tableau dashboard project visualizes New York Airbnb data from 2008 to 2015, highlighting room and property types by rating using bar charts, listing density via a bubble map, room type distribution with a pie chart, host growth over the years in a line graph, and the variety of property types using a word cloud, including unique options like boats and castles.

Geospatial Accidents By District

-Python

This python project analyzes and visualizes geographical data, specifically by creating a cluster map to highlight the district experiencing the highest number of accidents. It involves manipulating geospatial data, using Pandas for data handling and Folium for mapping clusters of accidents based on their locations.

GDP and Internet Usage 

- Python

This project methodically analyzes UN data on GDP per capita and internet usage, employing Python for comprehensive data cleaning, visualization, and exploration, revealing significant trends and insights into the complex relationship between economic prosperity and digital access across various countries.