Mr. sai k ponnekanti

Streaming Analytics and Real-Time Decision Making: The New Frontier of Data Processing

Abstract:

Streaming analytics has emerged as a critical competitive advantage in today's data-driven world, enabling organizations to process high-velocity data from diverse sources like e-commerce clickstreams and IoT sensor networks in real time. This article explores the fundamental concepts, architectural paradigms, and technological innovations driving real-time data processing systems. It examines the distinction between micro-batching and true streaming approaches, the challenges of time management in continuous data flows, and techniques for handling out-of-order events. The article details how leading organizations apply these technologies to mission-critical use cases, including fraud detection, recommendation engines, and operational dashboards. It further evaluates both cloud-native services from major providers and open-source frameworks, highlighting their respective strengths and limitations. The article concludes with architectural considerations for building robust streaming systems, covering essential components from data ingestion through processing to output integration.

Profile:

I’m Sai Kaushik Ponnekanti, a data engineering and ML-infrastructure leader with over 11 years of hands-on experience building scalable, high-throughput systems at companies like Meta, Google, Walmart Labs, Drawbridge, and CA Technologies. My work spans end-to-end data-pipeline design—handling petabytes with Hadoop, Spark, Kafka, and Beam—to privacy-compliance and monitoring frameworks that support thousands of active projects and queries. I hold an M.S. in Computer Science from USC and a B.Tech from BITS Pilani, and I frequently serve as a reviewer for data-systems research, bringing both deep technical insight and practical industry perspective to the evaluation of new work."