What is AWS IoT Analytics?
AWS IoT Analytics is a managed service for processing, enriching, and analyzing IoT data. The service handles the complexity of data preparation: cleaning noisy sensor data, filling data gaps, and calculating derived metrics.
IoT Analytics stores time series data in optimized data stores and enables SQL-based queries as well as Jupyter notebook analysis. Integration with SageMaker makes ML-based predictions directly on IoT data possible.
Core Features
- Pipelines for data cleaning, transformation, and enrichment
- Time series data store with automatic partitioning
- SQL datasets for recurring analyses
- Jupyter notebooks with pre-installed libraries
- Integration with QuickSight for dashboards
Common Use Cases
Predictive Maintenance: Sensor data from machines is analyzed to predict failures. ML models recognize patterns indicating upcoming maintenance before critical failures occur.
Fleet Management: Telemetry data from vehicles or devices is aggregated and analyzed. Dashboards show fleet health, usage patterns, and optimization potential.
Quality Control: Production data is analyzed in real-time to detect quality deviations early and reduce scrap rates.
Benefits
- No infrastructure management for data pipelines
- Automatic scaling with growing data volumes
- Native integration with AWS IoT Core
- SQL-based analytics without data engineering expertise
Integration with innFactory
As an AWS reseller, innFactory supports you with AWS IoT Analytics: pipeline design, data store optimization, ML model integration, and dashboard development with QuickSight.
Typical Use Cases
Frequently Asked Questions
What is AWS IoT Analytics?
AWS IoT Analytics is a managed service for processing and analyzing IoT data. The service provides pipelines for data cleaning, data stores for historical data, and Jupyter notebooks for analysis. IoT Analytics integrates seamlessly with IoT Core.
How does IoT Analytics differ from Kinesis?
IoT Analytics is optimized for IoT workloads with built-in data cleaning and time series storage. Kinesis is a generic streaming service. For pure IoT analytics, IoT Analytics is simpler; for complex stream processing pipelines, Kinesis is more flexible.
Can I use Machine Learning with IoT Analytics?
Yes, IoT Analytics integrates with SageMaker. You can train ML models on IoT data and run containerized models for batch inference in IoT Analytics. Ideal for predictive maintenance and anomaly detection.
What does AWS IoT Analytics cost?
Costs are based on: data ingestion (0.20 USD per GB), pipeline activities (0.20 USD per GB processed), data store (0.03 USD per GB/month), dataset creation (1 USD per GB scanned). Typical costs for medium-sized IoT fleets: 50 to 200 USD/month.