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retail-sales-data

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This project focuses on predicting retail sales using historical sales data and time-series regression techniques. It leverages Python, Scikit-learn, and XGBoost to build predictive models capable of forecasting sales trends. The goal is to provide actionable insights to retailers for inventory and sales strategy planning.

  • Updated Jun 11, 2025
  • Jupyter Notebook
Retail-sales-analyze-project

This project is an end-to-end retail sales analytics workflow created using uncleaned real-world retail data. The main objective was to clean messy raw data, prepare it for analysis, build meaningful KPIs using SQL, and create an interactive Power BI dashboard that provides insights into customer behavior, sales performance, and product trends.

  • Updated Dec 12, 2025
  • Python

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