Real-Time Analytics Pipeline for IoT Device Monitoring and Reporting
Overview
Experience | In Person |
---|---|
Type | Breakout |
Track | Data Engineering and Streaming |
Industry | Energy and Utilities |
Technologies | AI/BI, DLT, Unity Catalog |
Skill Level | Intermediate |
Duration | 40 min |
This session will show how we implemented a solution to support high-frequency data ingestion from smart meters. We implemented a robust API endpoint that interfaces directly with IoT devices. This API processes messages in real time from millions of distributed IoT devices and meters across the network.The architecture leverages cloud storage as a landing zone for the raw data, followed by a streaming pipeline built on DLT. This pipeline implements a multi-layer medallion architecture to progressively clean, transform and enrich the data.
The pipeline operates continuously to maintain near real-time data freshness in our gold layer tables. These datasets connect directly to Databricks Dashboards, providing stakeholders with immediate insights into their operational metrics.
This solution demonstrates how modern data architecture can handle high-volume IoT data streams while maintaining data quality and providing accessible real-time analytics for business users.
Session Speakers
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Padraic Kirrane
/Data Scientist
CK Delta
Nayan Sharma
/Lead Data Engineer
CKDelta