Building a Cloud-Based Data Engineering Pipeline for AI-Powered Customer Analytics - Mahendra Pudi, (International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2024)
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.
Keywords: Cloud-Based Data Engineering; Retail Analytics Architecture; AI-Powered Customer Analytics; Real-time Performance Monitoring; Scalable Data Processing Infrastructure