Olist Open Source Projects

Data analysis about Brazilian e-commerce business Olist

In this analysis, our group looked at data from the years 2016-2018 of 100,000 orders placed on the Brazilian eCommerce platform, Olist. We used the Random Forest machine learning algorithm to create a web app that predicts customer review scores using the most highly correlated features from the data as user inputs.

SQL queries from a Kaggle notebook I wrote to showcase some of the capabilities of SQL for data analysis.

Repository from the project "Genius" created at the Megahack 2.0 Hackaton by shawee

Projeto final da disciplina Estatística I do curso Santander Coders em parceria com a AdaTech ministrada pelo professor Damodara Barbosa.

Olist Brazil - Sales Insights and Machine Learning Predictions 📊🤖 Developed sales dashboards and machine learning models to analyze customer behavior and product performance for Olist, a Brazilian e-commerce platform. Utilized Power BI for visualization and multiple machine learning algorithms to predict customer satisfaction. 🔍📈

This analysis is the project of the Platzi Master Cohort 10 BI group. We will use the data published by Olist , in which we will answer how the socio-economic context of Brazil influences the purchase of products online.

onShop API

Final Data Science group project for Henry Bootcamp. Developed data solutions for Olist, an ecommerce brazilian startup, including a Dashboard in PowerBI, a forecasting model deployed on Streamlit and a web app for remote access.

To analyze an Olist dataset from multiple dimensions: from orders, customers, sellers, products, payment, price, geological location ,customer’s reviews and provide business Insights

Project developed for the course Data Mining at UFSC

Analysis of around 100.000 orders from a Brazilian online store

Projeto de Data Lakehouse com o dataset Brazilian E-Commerce Public Dataset by Olist

Análise do dataset da Olist

Insight from olist corporate analysis

A Comprehensive Time Series Analysis for Dynamic Sales Forecasting

Segmentation de la clientèle de Olist.