Keynote: Modern Data & Analytics Architecture: Solving the Real-Time Challenge

Today’s high-speed operational and AI-driven decision making requires ultra-fast analytics. Although typical data architectures are able to process streaming data, more often than not, the analytics are performed offline in batch mode. The real-time data is available for analysis, but the benefits of real time are lost the instant the data lands in a datastore or lakehouse for analysis. Ahuja delves into a modern data and analytics architecture—the Unified Real-Time Data Platform—that solves the real-time challenge. He shares details and use cases on how to process streaming data, enrich it with contextual historical data, and execute advanced analytical workloads—all at ultra-low latencies and massive scale.

Speaker:
Lalit Ahuja, Chief Technology Officer, GridGain Systems, Inc.