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Building a Cloud-Based Data Engineering Pipeline for AI-Powered Customer Analytics

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  • Mahendra Pudi

Abstract

This article comprehensively examines implementing a cloud-based data engineering pipeline for AI-powered customer analytics in the retail sector. It explores the architecture of advanced analytics solutions, their implementation strategies, and their impact on modern retail environments. The article details the development of a sophisticated system architecture encompassing data integration, processing pipelines, and machine learning capabilities, along with best practices for data quality, security, and scalability. It demonstrates how cloud-based analytics platforms can significantly improve customer engagement, reduce churn, enhance marketing effectiveness, and drive operational efficiency through real-world implementation examples and performance metrics. The article provides valuable insights into the transformative potential of AI-powered analytics in retail operations, highlighting key considerations for organizations undertaking similar digital transformation initiatives.

Suggested Citation

  • Mahendra Pudi, 2024. "Building a Cloud-Based Data Engineering Pipeline for AI-Powered Customer Analytics," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 10(6), pages 1482-1493, November.
    • Handle: RePEc:jbh:ijsrcs:v10:y2024:i6:id:543
    DOI: 10.32628/CSEIT241061186
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT241061186
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