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A detialed analysis on the customers, products, orders and shipments of the Brazilian E-commerce giant 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.
This repository contains SQL code for Olist database analysis using PostgreSQL
Database course lab work with Olist dataset
analysis and visualization focuses on orders and transactions that occurred at olist during 2017 and 2018.
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.
O repositório apresenta o conjunto de dados disponibilizado na plataforma do Kaggle, pela maior loja de departamento de marketplaces brasileiros, que conecta pequenas empresas de todo Brasil, os comerciantes podem vender seus produtos por meio da Olist Store e enviá-los a seus clientes. O conjunto de dados tem informações de 100 mil pedidos, ent…
Project for Data Science course on Santander Coders 2023.2/Ada
🔍 Analyze the Brazilian Olist E-Commerce Dataset to uncover sales trends, product performance, and customer insights for data-driven business decisions.
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