Analytics engineering platform for the Olist e-commerce dataset, built with dbt, BigQuery and GCP. Phase 2 of a data warehouse project.
Data warehouse project using PostgreSQL and Medallion Architecture to model and analyze 100k+ orders from the Olist Brazilian E-Commerce dataset.
Esse projeto utiliza dados da Olist para importar, tratar e analisar quatro bases de dados com o Power Query no Power BI. O objetivo é fornecer insights valiosos sobre vendas e comportamento do cliente nos principais marketplaces do Brasil.
This project implements a Data Engineering pipeline using the Databricks Lakehouse platform. The pipeline ingests raw data from Cloudflare R2 object storage, processes it using scalable ingestion mechanisms, and transforms it into structured datasets for analytics.
Olist E-Commerce Funnel & Retention Analysis
Advanced SQL analysis of the Olist Brazilian E-Commerce dataset.
Este projeto utiliza o Power BI para importar, tratar e analisar dados da Olist, gerando insights sobre vendas e comportamento dos consumidores a partir de quatro bases distintas.
End-to-end analytics of Olist dataset showing insights on customers, sellers, and deliveries.
Build a SQL Server Data Warehouse analyze Olist's E-ecommerce performance for inventory, marketing and logistics insights
A Medallion Architecture ETL pipeline for the Brazilian Olist E-commerce dataset. Orchestrates raw data ingestion into SQLite (Bronze), automated data quality validation via Great Expectations, transformation into optimized Parquet files (Silver), and the generation of business-ready analytical reports (Gold) using Polars.
Analyzed real-world e-commerce data to uncover insights on sales, customer behavior, and delivery performance. Built using Python for data cleaning, SQL for analysis, and Power BI for visualization.
End-to-end data science project on ~100k Brazilian e-commerce orders — predicting churn risk customers with XGBoost, an interactive Dash BI dashboard, and a GPT-4o-mini powered customer recovery email agent.
An insightful data analysis project on the Olist Store e-commerce dataset, focused on uncovering trends in customer behavior, payment methods, delivery performance, and satisfaction levels. The project integrates Excel, Power BI, Tableau, and MySQL for data processing, visualization, and reporting.
End-to-end ML project focusing on predicting E-Commerce customer dissatisfaction using logistical data. Built with PostgreSQL, Python and Streamlit.
Análisis operativo y salud financiera del e-commerce brasileño Olist. Incluye la automatización de la creación de la base de datos en MySQL, validación estadística de estacionalidad (ACF/PACF) y dashboards estratégicos para la optimización logística.
SQL project based on the Brazilian e-commerce dataset (Olist). Includes MySQL database design, table creation scripts, ER diagram, and a complete set of queries ranging from basic operations to advanced subqueries.
Delivery and logistics performance diagnostic dashboard built for the Olist e-commerce platform
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