Google Cloud Digital LeaderDigital transformation with Google CloudHard
A global automotive manufacturer is seeking to digitally transform its supply chain operations. They need a solution to collect, process, and analyze real-time data from thousands of IoT sensors on manufacturing equipment and logistics vehicles across multiple continents. The solution must handle high-volume streaming data, perform immediate anomaly detection, and integrate with existing enterprise resource planning (ERP) systems for proactive maintenance and optimized logistics. Which Google Cloud service combination would be most effective?
- ACloud Storage, Cloud Run, Cloud Monitoring
- BCloud Spanner, Compute Engine, App Engine
- CCloud SQL, Cloud Functions, Cloud CDN
- DCloud IoT Core, Pub/Sub, Dataflow, BigQuery
Show answer & explanationAnswer & explanation
Correct answer: D. Cloud IoT Core, Pub/Sub, Dataflow, BigQuery
Cloud IoT Core is essential for securely connecting and managing a large fleet of IoT devices. Pub/Sub handles high-volume real-time data ingestion. Dataflow provides stream processing for immediate anomaly detection and data transformation. BigQuery is then used for scalable storage and analytics of the processed data, enabling integration with ERP for proactive insights.
Why the other options are wrong
- A. This combination provides object storage, serverless containers, and monitoring, but lacks the dedicated IoT device management and powerful stream processing capabilities required.
- B. This combination is for globally consistent databases, VMs, and web applications, not specifically for an IoT data pipeline with real-time processing.
- C. This combination is for transactional databases, serverless functions, and content delivery, not for high-volume IoT streaming data processing.
Google Cloud IoT Data Pipeline
A series of Google Cloud services designed to efficiently ingest, process, store, and analyze data from Internet of Things (IoT) devices at scale.
- Enables real-time data collection from distributed sensors.
- Supports high-volume streaming data processing.
- Facilitates anomaly detection and predictive maintenance.
Memory trick: IoT Core connects, Pub/Sub collects, Dataflow deflects, BigQuery inspects.