Acquiring data from IoT devices without extracting actionable insights renders the entire process ineffective. Raw data holds potential, but only through timely processing, contextualization, and visualization does it generate real value. In modern cloud ecosystems, Microsoft Azure and Amazon AWS offer robust, scalable platforms to ingest, process, analyze, and present IoT data.

This session will focus specifically on the ingestion and real-time analysis layer of an IoT analytics pipeline. We’ll explore how to establish a secure, scalable, and resilient streaming architecture using typical messaging and streaming services provided by Azure and AWS. Topics will include event ingestion from devices at scale, transformation pipelines, data filtering, and routing logic. We will also dive into the operational patterns for ensuring data consistency, low-latency delivery, and high-throughput processing.

Real-time intelligence is a cornerstone of modern IoT applications, enabling instant feedback, alerting, and adaptive automation. Through practical guidance and architecture diagrams, we will examine how to implement a complete end-to-end solution—from device telemetry to real-time dashboards and long-term storage—on both Azure and AWS platforms.

Attendees will leave with a solid understanding of how to architect real-time IoT analytics solutions using native cloud services, and how to choose between offerings based on project requirements and platform capabilities.

Turn raw IoT data into real-time insights with powerful ingestion and analytics on Azure or AWS. Learn how to build a complete end-to-end solution using native messaging and streaming services to drive intelligent, responsive applications at scale.