Building an IoT Data Management Pipeline with AWS and MongoDB

This session explores how to leverage Amazon Web Services (AWS) to establish and manage a MongoDB database for storing, processing, and analysing Internet of Things (IoT) sensor feeds. Participants will learn how to collect real-time sensor data, transmit it securely through AWS IoT Core, and integrate it with MongoDB Atlas for scalable database management. The session will demonstrate how AWS services such as AWS Lambda, Amazon S3, and Amazon CloudWatch can support data ingestion, automated processing, storage, monitoring, and system reliability.
Through a practical, step-by-step workflow, participants will explore how to structure sensor readings, manage timestamps, track equipment performance, and prepare IoT data for dashboards, predictive maintenance, operational reporting, and decision-making. The session is relevant to engineers, developers, data professionals, and IoT innovators seeking to build secure, scalable, and cost-effective data management solutions for applications such as industrial machinery, petroleum pumps, smart agriculture, energy systems, and environmental monitoring.

Key learning outcomes are -

• AWS setup: Configure the cloud infrastructure required to receive IoT sensor feeds.
• MongoDB integration: Connect AWS services to MongoDB Atlas for storing structured and semi-structured sensor data.
• Real-time data pipelines: Collect, validate, transform, and store readings from connected devices.
• Security and monitoring: Apply access controls, secure connections, logging, and performance monitoring.
• Data-driven insights: Prepare sensor data for analytics, visualisation, predictive maintenance, and operational reporting.