Proficient in SQL and Tableau. Currently pursuing a Micromaster's in Statistics and Data Science from MIT, complementing proficiency in English with French studies. Seeking opportunities to apply creativity and analytical skills in challenging environments, contributing to innovative solutions through data utilization.
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In this project, I demonstrate the automation of analysis reporting via Slack using SQL, Python, and Datalab, streamlining processes and providing real-time insights to stakeholders.
In this project, I employ comprehensive string cleaning techniques to refine and organize a database containing crucial information on Astronauts' Extra Vehicular Activities (EVAs).
Harnessing the power of SQL window functions and sophisticated statistical analyses, delve into manufacturing data to discern instances where adjustments may have been suboptimal for the organization's objectives.
Utilized SQL to analyze and explore content from leading streaming platforms including Amazon Prime, Hulu, Netflix, and Disney+.
Analyzing NASA's planetary exploration budgets from 1960 to 2035, including inflation adjustments and identifying the most expensive missions. The analysis also explores annual expenditure trends and budget allocation by destination, revealing shifts from the moon to Mars and outer planets over time.
This project explores a 2022 survey aimed at understanding the growth perceptions of Finnish companies, alongside their assessment of the pandemic's impact on growth. Through dataset analysis, it seeks to reveal valuable insights into growth trajectories and managerial perspectives.
Streit, a REIT, aims to transform West Ridge North into a premier residential destination in Downtown Detroit through rigorous financial analysis using Excel.
The Wake County Watchdog team aims to provide insight into fiscal management by presenting a detailed analysis of expenditures against budget allocations for the current fiscal year. To ensure accessibility and inclusivity, a Power BI theme named "Colorblind safe" was implemented, addressing the needs of individuals with color vision deficiencies.
Within this case analysis, SQL has been employed to address queries pertaining to finance and logistics.
SQL project analyzing high-growth trends for investment firms, utilizing simulated data to provide strategic insights and optimize portfolio decisions.
This SQL project aims to analyze data collected by a Japanese international university regarding the mental health of foreign students. Leveraging data manipulation techniques, it seeks to identify the factors with the most significant impact on this crucial aspect of their overseas experience.
This project employs SQL skills to analyze a dataset focused on product emissions, which comprise over 75% of global emissions. Its aim is to discern the industries primarily responsible for these emissions, providing insights into the most significant contributors to environmental impact.
This project analyzes international debt data collected by the World Bank using SQL. It explores the total debt amount owed by countries, identifies the country with the highest debt, and examines the average debt across different indicators.
This SQL project explores data from BusinessFinancing.co.uk on the world's oldest businesses, focusing on their founding dates and industries. Through joining techniques and manipulation tools like grouping and filtering, we uncover insights into these enduring businesses' longevity and resilience amidst changing market conditions.
This SQL project delves into video game critic and user scores, alongside sales data, for the top 400 video games released since 1977. Exploring trends in gaming quality and sales, it seeks to uncover whether the golden age of video games is past or present.
This SQL project analyzes data from the U.S. Social Security Administration spanning over a hundred years to understand American baby name preferences. It showcases SQL skills applicable across various domains, from name research to business trend analysis.
Leveraging both Python and SQL, this project merges and explores Olympics datasets, enriching them with country details and utilizing pandas for insightful analysis, culminating in dynamic visualizations with plotly.
In this Python endeavor, I analyze standardized test performance data from NYC's public schools. My aim is to identify schools with top math results, explore performance variations by borough, and ultimately uncover the city's top ten performing schools!
In this project, I applied my Python skills to tackle a real-world question: are Netflix's movies getting shorter over time? Utilizing various techniques from lists and loops to pandas and matplotlib for an exploratory data analysis.
In this SQL project, I crafted a comprehensive query aimed at evaluating the net revenue generated across various product lines. Additionally, I conducted in-depth analyses focusing on date-specific trends and warehouse locations.
Using Excel, I merged admission and discharge datasets from Yale New Haven Health System, enabling insights for resource allocation and patient care.
Utilizing a rich dataset spanning 1980 to 1996, the project aims to craft a dimensional data model and build a data transformation pipeline, embracing the Kimball method to unlock actionable insights and drive innovation.
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