Amirtharaj Sathees Chandran

Healthcare Analytics: Designing In-Memory Distributed Systems for Billion-Row Claims Data at Scale

Abstract:

At a billion-row scale, cohort- and join-heavy healthcare batch workloads bottleneck platforms that must serve governed reporting and faster analytics. This session presents in-memory distributed execution and portable containerized pipelines—from partitioning through claims-heavy batches with supporting reference joins—with practical focus on throughput, parallel memory control, elasticity, overlapping batch cycles, and restrained benchmarking claims.

Profile:

Amirtharaj Sathees Chandran brings over twenty years of experience in distributed systems, cloud platforms, and regulated healthcare analytics; he has led multiple data-intensive platforms from architecture through production. His expertise includes high-throughput batch analytics, in-memory distributed execution, containerized services, pipelines at extreme row scale, global master data, and metadata systems for consumer-scale search. He has contributed to large programs across the United States and India for leading life sciences analytics organizations and for Fortune 500 enterprises across telecommunications, media, retail, and technology—improving performance, reliability, and operational efficiency. As a Principal Engineer at IQVIA Inc., he aligns product, data, and operations stakeholders and promotes repeatable architecture practices that de-risk complex delivery.