End-to-end data analytics project using SQL and Power BI to analyze e-commerce sales performance.
Comprehensive data analysis of the Olist e-commerce dataset using PostgreSQL queries, Jupyter Notebooks, Excel models, and interactive Power BI dashboards for supply chain and sales insights.
AI-powered end-to-end e-commerce analytics platform integrating MySQL, advanced SQL modeling, executive BI dashboards (Power BI), and generative AI reporting to deliver insights on revenue growth, retention, operational efficiency, and customer lifetime value
Databricks SQL Medallion Architecture (Bronze-Silver-Gold) + Delta Lake powering a Power BI star schema -- surfaced $97.24K in e-commerce revenue leakage and a 26-day logistics outlier.
End-to-end e-commerce analysis using PostgreSQL & Excel to evaluate product yield, geographic logistics, and delivery delay impacts on CSAT.
Customer segmentation project using RFM (Recency, Frequency, Monetary) analysis on the Brazilian E-Commerce (Olist) dataset to identify high-value customer behaviors.
SQL-driven customer analytics dashboard built on the Olist Brazilian E-Commerce dataset. Answers four business questions — RFM segmentation, cohort retention, product affinity, and revenue leakage — using MySQL queries served via FastAPI and visualized in Next.js with Recharts.
End-to-end e-commerce sales analysis using MySQL on the Olist dataset to analyze revenue, orders, customers, monthly trends, repeat customers, and business KPIs.
Análise de e-commerce e logística do dataset Olist com tratamento em Python/SQL, prototipação no Figma e dashboard interativo no Power BI.
Olist Multi-Modal E-Commerce Analytics，涵盖数据探索、地理、情感、评分预测、客户细分、生命周期与流失，融合ML/DL及RFM/K-Means/BTYD模型
Operational and customer-experience intelligence over the Olist Brazilian E-Commerce dataset. DuckDB/PostgreSQL warehouse, data-quality contracts, NLP over reviews, FastAPI serving layer.
End-to-end data analysis investigating the impact of delivery delays on customer retention for Olist e-commerce using Excel, SQL Server, and Power BI.
Big data analytics on e-commerce datasets including Brazilian Olist marketplace data — data processing, insights, and exploratory analysis.
End-to-end e-commerce analytics pipeline using PostgreSQL, SQL quality tests, Python, Streamlit, and the Olist dataset.
Analyzes 100K+ e-commerce transactions to uncover key business challenges like low customer retention and delivery delays using Python, SQL, and MySQL
Predicts the probability of late delivery for Brazilian e-commerce orders using XGBoost, built on the Olist dataset. Includes full EDA, a leakage-safe ML pipeline (SMOTE, feature selection, cross-validation), and a deployed Streamlit app for real-time risk scoring.
End-to-end e-commerce analysis of 100k+ Olist orders using Excel, Power Query, SQL, and Tableau Public.
Interactive analytics dashboard for Brazilian e-commerce data (Olist dataset)
Python-based data cleaning, validation, and exploratory analysis of all 9 tables in the Brazilian E-Commerce Olist dataset.
Automated ETL pipeline for Olist e-commerce data analysis using PostgreSQL, Python, and SQL.
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