Architecting Sub-Second Analytics Pipelines

Learn to design and implement high-performance analytics pipelines capable of processing data in sub-second timeframes in this 27-minute conference talk from Conf42 ML 2025. Explore the fundamental challenges of real-time machine learning, beginning with understanding the data explosion problem and comparing batch versus streaming processing approaches. Examine practical applications through detailed case studies including real-time fraud detection systems in financial services, personalization engines for e-commerce platforms, and predictive maintenance solutions in manufacturing environments. Discover the technical challenges inherent in real-time ML implementations and gain insights into selecting appropriate streaming frameworks for your specific use cases. Master the principles of implementing robust real-time architecture that can handle high-velocity data processing while maintaining accuracy and reliability in production environments.