Alexis Brito

Watching the World Baseball Classic, I got caught up in the national pride of it all: the Dominican power hitters, the Venezuelan infielders, the precision of the Japanese roster. It made me wonder which countries actually produce the best baseball players, and how each nation's style shows up in the numbers. This dashboard compares the career stats of 34 legendary players across 8 countries, letting you filter by country and switch metrics to see where the game's greatest talent comes from. Tools: Tableau Public, Python (Pandas). Data: Baseball Reference / Baseball Almanac.

Interactive

Interactive Dashboard

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Every business that holds inventory lives with the same quiet tension: hold too much and cash freezes on the shelf; hold too little and you lose the sale. My earlier projects mostly described what happened — I wanted to build something that points to a decision. So I took a specialty-foods distributor's operational data (77 products, 29 suppliers, 3 carriers, ~830 orders spanning 1996–1998) and built an end-to-end pipeline answering the four questions leadership actually asks: where is cash trapped, where are we about to run out, which suppliers can we lean on, and are we overpaying to ship? I modeled six related tables in MySQL, wrote eight analytical queries (inventory turnover, stock-out risk, supplier lead time, a weighted 0–100 supplier score, slow-moving stock, and freight optimization), exposed the results as reporting views, and visualized them in an interactive Power BI dashboard. Tools: MySQL 8, SQL (CTEs, window functions, NTILE, weighted scoring), Power BI (DAX). Data: Northwind sample database.

Ingested and cleaned a record Citi Bike dataset using Pandas, resolving missing values and standardizing schema. Performed EDA to uncover ridership trends, peak usage windows, and station-level demand patterns. Produced charts delivering actionable recommendations for bike redistribution.

Peak Usage Hours

Average Trip Duration

Station Imbalance Analysis

Top Routes

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Designed a multi-dimensional statistical matching algorithm to identify ideal basketball recruits from large player datasets. Built a scoring engine ranking candidates on shooting efficiency, defensive rating, and positional versatility.

Sixth Man Class Diagram

Detailed Class Diagram

Enter Player Stats — Sequence Diagram

Update Player Stats — Sequence Diagram

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Built a comprehensive MLB data pipeline scraping baseball statistics from Baseball Reference across 5 years (2020-2024). Engineered four specialized scrapers for team batting, standings, and player pitching/batting data. Cleaned and normalized raw data, reducing inconsistencies by over 90%. Created data visualizations answering key questions about player performance and team success.

Top 5 Home Run Hitters by Season

Team OPS Leaders by Season

Consecutive 100+ Win Seasons

Top 5 Strikeout Leaders by Season

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