Salvato in:
| Autore principale: | |
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| Natura: | Recurso digital |
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| Pubblicazione: |
Zenodo
2025
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| Accesso online: | https://doi.org/10.5281/zenodo.17466536 |
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Sommario:
- <h2> Project Overview</h2> <p dir="auto">This repository contains the full implementation and documentation of my Master’s thesis,<br><strong>“Design and Implementation of an End-to-End Data Engineering Pipeline for E-Commerce Analytics.”</strong></p> <p dir="auto">The project demonstrates how a <strong>lightweight, automated data engineering pipeline</strong> can transform raw e-commerce data into actionable business insights.<br>The research emphasizes <strong>cost-effective, scalable analytics</strong> using <strong>open-source tools</strong> — making advanced data-driven decision-making accessible for small and medium-sized enterprises (SMEs).</p> <div dir="auto"> <h2> Research Findings</h2> <a href="https://github.com/Priyanka-KP-DA/ecommerce-data-pipeline#-research-findings"></a></div> <p dir="auto">The developed pipeline successfully automated the extraction, cleaning, and transformation of the data, reducing manual preparation time by approximately <strong>85%</strong>.<br>Through Power BI visualization, it enabled insights into <strong>sales trends</strong>, <strong>customer segmentation</strong>, and <strong>product performance</strong>, demonstrating that even small e-commerce firms can achieve data-driven intelligence using open-source tools.</p>