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Answer: Cloud Pub/Sub, Cloud Dataflow, BigQuery
The correct sequence is **Cloud Pub/Sub, Cloud Dataflow, BigQuery**. This stack is ideal for IoT data handling because: 1. **Cloud Pub/Sub** offers a globally durable message ingestion service, perfect for streaming data from IoT devices. 2. **Cloud Dataflow** provides a managed service for processing data in various ways, including streaming computation, making it suitable for high-volume data processing pipelines required in IoT scenarios. 3. **BigQuery** serves as a fully managed data warehouse with a SQL interface, allowing for efficient storage and analysis of IoT data alongside other enterprise analytics. - **Option B** is incorrect due to the wrong order of services. - **Option C** is incorrect because Cloud Dataproc is not the ideal tool for analysis in this context; it's more suited for running Apache Spark and Hadoop clusters. - **Option D** is incorrect as App Engine is not designed for IoT data ingestion.
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Imagine you're tasked with handling streaming data from thousands of IoT devices. The goal is to ingest this data, process it through a pipeline, and store it for analysis, enabling SQL queries. Which sequence of Google Cloud services would best accomplish this task?
A
Cloud Pub/Sub, Cloud Dataflow, BigQuery
B
Cloud Dataflow, Cloud Pub/Sub, BigQuery
C
Cloud Pub/Sub, Cloud Dataflow, Cloud Dataproc
D
App Engine, Cloud Dataflow, BigQuery