Interactive Tableau dashboard for analyzing Superstore sales, profit trends, top products, customer segments, and regional performance.

Proyecto de análisis de ventas de tiendas para Alura Latam con Python y visualización de datos.

Interactive Tableau dashboard for analyzing Superstore sales, profit trends, top products, customer segments, and regional performance.

Statistical and machine learning analysis of coffee bean prices using R. Includes EDA, ANOVA, and Lasso regression to understand how origin, roast, and ratings influence pricing.

This repository features the Retail sales and customer insights dashboard demonstrating data cleaning and analysis using Excel, Python, and SQL, along with interactive visualization in Power BI. Explore the code and reports to gain insights into sales performance, customer behavior, and product trends. A complete end-to-end data analytics workflow

End-to-end Exploratory Data Analysis (EDA) project on Superstore Sales dataset including data cleaning, feature engineering, outlier handling, customer segmentation, and business insights using Python, Pandas, Matplotlib, and Seaborn.

E-Commerce Sales Analysis

📖Datamart Analysis with Machine Learning [ML] 🤝Shared ⭐R Shiny 🌐App📚Learning ✅Deployed

Confidence interval comparison for average Apple prices across two cities using Python.

Superstore Sales Analysis project using Python, Pandas, Matplotlib, Seaborn, KPI Analysis, EDA, Customer Segmentation, and Business Insights.

A basic end-to-end retail data analytics and machine learning project using Python, including data cleaning, visualization, business insights, and quantity prediction

Retail sales SQL analysis – 20 business-oriented queries (revenue, customers, geography, seasonality, payments, inventory) with insights & recommendations

Optimasi strategi diskon menggunakan data Superstore.

Segmentasi pelanggan menggunakan data Superstore.

business-oriented analytics project using Python and SQL to answer customer, product, and regional performance questions from a fictional retail dataset

A SQL-based deep dive into Zepto's retail data to optimize inventory, pricing strategies, and revenue forecasting.

Interactive Store Sales Analysis Dashboard built using Power BI to analyze sales performance, profit trends, category insights, and regional distribution for data-driven business decisions.

This Power BI project explores the story behind retail sales data, transforming numbers into insights. The dashboard reveals key trends in sales performance, revenue growth, and customer demographics, helping decision makers identify profitable channels, boost customer retention, and optimize business growth.

This project explores retail chain performance in New Zealand by combining sales forecasting, regional sales analysis, and supply chain insights. Using real data and Python (including Prophet for forecasting), it uncovers patterns and helps identify areas for improvement in inventory and operations.

End-to-end retail customer segmentation using RFM analysis, K-Means clustering, and an interactive Streamlit dashboard for business insights.