I turn raw, messy data into clear, decision-ready insights from cleaning 541K+ row datasets in Python to building a 14-table relational data model and 5-page Power BI report analyzing $262M in logistics revenue.
Data Cleaning & Validation Data Health Analysis Exploratory Data Analysis
Relational Data Modeling DAX Measures Query Optimization Business Insight Reporting
ποΈ SQL Projects
SQL fundamentals through advanced querying across 3 real-world datasets aggregation,
self-joins, subqueries, window functions (RANK, ROW_NUMBER), and query optimization
with EXPLAIN/indexing.
π Python Projects Cleaning and analyzing a 541K-row e-commerce transactions dataset and Netflix's full content catalog using pandas missing data handling, outlier checks, and 10+ visualizations.
π Excel & Power BI Projects Progression from spreadsheet-level cleaning to a full BI capstone: a 14-table relational data model, custom DAX measures, and a 5-page interactive report analyzing $262M in logistics revenue across fleet, driver, and safety operations.