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Explore comprehensive retail analysis and insights focusing on Marley International Store, powered by data analytics techniques and visualizations using Python, PowerBI and Jupyter Notebooks.

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Data Analytics Project

This repository serves as a comprehensive showcase of my data analytics projects, with a primary focus on retail analysis and insights. It includes a detailed analysis of Marley International Store, a prominent retail establishment, conducted using Power BI and Python.

Project Overview

The main objective of this project was to analyze the performance and trends of Marley International Store, leveraging data analytics and visualization techniques. The analysis encompassed various aspects of the store's operations, including sales trends, product categories, regional performance, and customer segmentation.


PowerBI Topology


Contents

  • Marley_International_Store_Data: Data used for the analysis.
  • Marley_International_Store_Presentation: PowerPoint presentation showcasing the detailed analysis and insights.
  • Methodology_documentation: A comprehensive outline of the methodology employed for the data analysis.
  • Findings and Insights: A summary of the key findings and actionable insights derived from the analysis.
  • Power BI Report: The published Power Bi report. Link to visit the Power-Bi report.
  • Python_Code: Alternative analysis conducted using Python. Link to Python analysis.

How to Use

Feel free to explore the repository and access the data and presentation files. The Power BI report provides an interactive and visually engaging overview of the analysis, highlighting essential insights and recommendations for Marley International Store. The Python script and Jupyter Notebook offer an alternative programmatic approach to the same analysis.


About Me

I am a passionate Solutions Architect and Data Engineer with a keen interest in leveraging data-driven strategies to drive business growth and innovation. My expertise lies in data visualization, exploratory data analysis, and deriving actionable insights from complex datasets.

Contact Information

For any inquiries or collaboration opportunities, please feel free to reach out and connect with me on LinkedIn.

Thank you for visiting my Data Analytics Portfolio repository!