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

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

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.

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

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

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

End-to-end retail analytics using SQL and Power BI. Analyzed $2.27M retail revenue using SQL and Power BI to uncover customer behavior, retention patterns, product performance, profitability drivers, and sales trends.

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.

End-to-end Business Intelligence project using Python, EDA, RFM Customer Segmentation, and Tableau Dashboards on 1M+ e-commerce transactions.

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

E-Commerce Sales Analysis

Excel data analysis project: cleaning retail sales data, creating pivot tables, and building an interactive dashboard

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

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

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

Optimasi strategi diskon menggunakan data Superstore.

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.

Statistical analysis of US customer spending behavior and demographic segmentation. Tests real business assumptions using hypothesis testing, EDA, and data-driven insights.

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

Power BI Portfolio