Practice Test 3 | Google Cloud Certified Professional Cloud Architect | Dumps | Mock Test
You need to take streaming data from thousands of Internet of Things (IoT) devices, ingest it, run it through a processing pipeline, and store it for analysis. You want to run SQL queries against your data for analysis. What services in which order should you use for this task?
A. Cloud Dataflow, Cloud Pub/Sub, BigQuery
B. Cloud Pub/Sub, Cloud Dataflow, Cloud Dataproc
C. Cloud Pub/Sub, Cloud Dataflow, BigQuery
D. App Engine, Cloud Dataflow, BigQuery
Correct Answer C
Explanation
C (Correct answer) – Cloud Pub/Sub, Cloud Dataflow, BigQuery
Cloud Pub/Sub is a simple, reliable, scalable foundation for stream analytics and event-driven computing systems. As part of Google Cloud’s stream analytics solution, the service ingests event streams and delivers them to Cloud Dataflow for processing and BigQuery for analysis as a data warehousing solution. Relying on the Cloud Pub/Sub service for delivery of event data frees you to focus on transforming your business and data systems with applications such as:
· check Real-time personalization in gaming
· check Fast reporting, targeting and optimization in advertising and media
· check Processing device data for healthcare, manufacturing, oil and gas, and logistics
· check Syndicating market-related data streams for financial services
Also, Use Cloud Dataflow as a convenient integration point to bring predictive analytics to fraud detection, real-time personalization and similar use cases by adding TensorFlow-based Cloud Machine Learning models and APIs to your data processing pipelines. https://cloud.google.com/ml-engine/
BigQuery provides a flexible, powerful foundation for Machine Learning and Artificial Intelligence. BigQuery provides integration with CloudML Engine and TensorFlow to train powerful models on structured data. Moreover, BigQuery’s ability to transform and analyze data helps you get your data in shape for Machine Learning. https://cloud.google.com/bigquery/
Other solutions may work one way or other but only the combination of theses 3 components integrate well in data ingestion, collection, and real-time analysis, and data mining in a highly durable, elastic, and parallel manner.
A – Wrong order. You don’t normally ingest IoT data directly to DataFlow
C – DataProc is GCP version of Apache Hadoop/Spark. Although it has the SQL-like Hive, it does not provide SQL interface as sophisticated as BigQuery does.
D – App Engine is compute resources. It is not designed to ingest IoT data like PubSub. Also. It’s rare use case App Engine ingests data to DataFlow directly.
Below two pictures illustrate the typical toles played by DataFlow and PubSub
Dataflow
PubSub
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