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An IoT platform is providing services to home security systems. They have more than a million customers, each with many home devices. Burglaries or child safety issues are concerns that the clients customers. Therefore, the platform has to respond very quickly in near real time .
What could be a typical data pipeline used to support this platform on Google Cloud?
- A . Cloud Pub/Sub, Cloud Dataflow, Data Studio
B. Cloud Functions, Cloud Dataproc, Looker
C. Cloud Pub/Sub, Cloud Dataflow, BigQuery
D. Cloud Functions, Cloud Dataproc, BigQuery
Suggested Answer: A
Explanation:
Explanation
=> Cloud Pub/Sub- Cloud Pub/Sub is the best to be the end-point for ingesting large amounts of data. It will grow as required, can stream data to downstream systems, and can also work with intermittently available backends.
=> Cloud Dataflow- supports streaming data and therefore is an appropriate option for processing the data that is ingested.
=> BigQuery- BigQuery also supports streaming data and its possible to do real time analytics on it.
=> DataStudio- DataStudio and Looker are for visualization. They don't have any in-built analysis.
=> Cloud Functions- Cloud Functions is a useful serverless endpoint. However, Pub/Sub is better in this case because it can also retain messages for a set period if it was not possible to deliver it first time.
=>Cloud Dataproc- Cloud Dataproc is used for Hadoop/Spark workloads and won't be a good fit here.
Explanation:
Explanation
=> Cloud Pub/Sub- Cloud Pub/Sub is the best to be the end-point for ingesting large amounts of data. It will grow as required, can stream data to downstream systems, and can also work with intermittently available backends.
=> Cloud Dataflow- supports streaming data and therefore is an appropriate option for processing the data that is ingested.
=> BigQuery- BigQuery also supports streaming data and its possible to do real time analytics on it.
=> DataStudio- DataStudio and Looker are for visualization. They don't have any in-built analysis.
=> Cloud Functions- Cloud Functions is a useful serverless endpoint. However, Pub/Sub is better in this case because it can also retain messages for a set period if it was not possible to deliver it first time.
=>Cloud Dataproc- Cloud Dataproc is used for Hadoop/Spark workloads and won't be a good fit here.
Posted : 09/01/2023 5:28 pm