Production grade Supply Chain & Logistics Optimization platform handling 100,000+ records. Built with Star Schema, Advanced DAX, and AI Root Cause Analytics in Power BI.

End-to-end logistics operations analysis using Power BI, DAX and Power Query to track a $298M portfolio across revenue, fleet efficiency, and risk.

🏗️ Modern Analytics Engineering project using dbt and BigQuery to model fleet operations. Implementing a Medallion Architecture, it transforms raw GPS data into a reliable Star Schema. Focuses on resolving data quality issues like sensor noise and duplicates through automated testing and CI/CD to ensure production-grade reporting.

This margin analysis quantifies unrecovered profit, identifies loss making jobs, clients, and routes, and delivers clear recommendations to improve pricing and operational efficiency.

End-to-end logistics operations analytics project using SQL and Power BI. Built a relational database, created analytical views, and developed dashboards to analyze driver performance, revenue per trip, and on-time delivery trends.

Pipeline analítico de logística com PostgreSQL, dbt, Airflow e Streamlit para análise de SLA, performance regional e eficiência operacional aplicando arquitetura multicamadas e analytics engineering.

Analyzing global flight patterns, passenger volumes, and airline performance to identify travel trends and logistics bottlenecks

End-to-end analytics project for monitoring shipment performance, service quality, incidents, and customer experience in an express logistics context.

Supply chain analytics dashboard with Python, PostgreSQL and Power BI

An end-to-end retail intelligence system combining SQL database design and Power BI dashboards to track enterprise sales, inventory health, staff productivity, and shipment logistics

End-to-end SQL analytics case study solving 7 real supply chain business problems across 180,519 orders. delivery performance, profitability, regional sales, and more.

End-to-End Supply Chain Analytics Dashboard using SQL, Python, and Power BI. Analyzed inventory, supplier performance, logistics costs, shipping efficiency, and profitability KPIs through interactive business intelligence dashboards.

A Python-based decision support tool that forecasts short-horizon demand, evaluates capacity utilization risk, and produces prioritized mitigation actions with backtest accuracy (MAE/MAPE) and a professional PDF report.

Optimizing logistics dispatch schedules using Simple Linear Regression to forecast delivery times.

Comprehensive analysis of Brazilian E-commerce data: orders, deliveries, reviews, seller performance, and revenue insights.

End-to-end warehouse analytics system: SQL bottleneck detection, RandomForest delay prediction (ROC-AUC 0.876), and a 4-page Streamlit dashboard with automated business recommendations.

Real-time logistics monitoring system using Kafka, Spark Streaming, PostgreSQL, Docker, and Power BI for processing and visualizing live inventory and GPS data.

Análise de custos logísticos no e-commerce com foco na redução de frete e geração de insights financeiros (Potencial de~R$114 mil).

End-to-end Logistics Data Analytics project analyzing Delhivery shipment operations using Python, Feature Engineering, Data Cleaning, Aggregation, Statistical Analysis, Outlier Detection, and Business Insights to improve delivery performance.

Interactive Excel logistics dashboard tracking OTIF, SLA compliance, delay trends and return rates across 200 shipments — revealing a 42.5% SLA breach rate and 235% increase in delays from January to July.