Google Professional Data Engineer Question 147
Select 1Google Cloud PlatformYour company wants to implement a data pipeline for real-time analytics on customer transactions. The business requirements are as follows:
- Ingest data from multiple sources, including a mobile app, website, and point-of-sale systems.
- Process data in real time to detect anomalies in transactions.
- Store processed data for long-term analysis and reporting.
- Ensure scalability to handle varying data volumes during peak hours.
Which combination of Google Cloud services best maps to these business requirements?
- A
Cloud Pub/Sub for data ingestion, Dataflow for real-time processing, BigQuery for storage and analysis
- B
Cloud Storage for data ingestion, Dataflow for real-time processing, BigQuery for storage and analysis
- C
Cloud Pub/Sub for data ingestion, Dataproc for real-time processing, Firestore for storage and analysis
- D
Cloud Pub/Sub for data ingestion, Dataflow for real-time processing, Cloud Spanner for storage and analysis
- E
Cloud Pub/Sub for data ingestion, Dataflow for real-time processing, Bigtable for storage and analysis
Show answer and explanation
Correct answer: A
Explanation
To meet the business requirements, Cloud Pub/Sub is used for scalable and reliable data ingestion from multiple sources. Dataflow processes data in real time to detect anomalies, and BigQuery provides cost-effective, scalable storage and analysis of the processed data. This combination ensures real-time analytics, scalability, and support for long-term reporting.
- A. Correct.
Correct: Cloud Pub/Sub is suitable for scalable ingestion from multiple sources, Dataflow supports real-time data processing, and BigQuery is ideal for long-term storage and analytics.
- B. Incorrect.
Incorrect: Cloud Storage is not designed for real-time data ingestion; it is better suited for batch processing or archival storage.
- C. Incorrect.
Incorrect: Dataproc is used for batch processing with Hadoop/Spark, not real-time processing. Firestore is not the best choice for large-scale analytics.
- D. Incorrect.
Incorrect: Cloud Spanner is a relational database service optimized for transactional workloads, not analytics or long-term storage.
- E. Incorrect.
Incorrect: Bigtable is a NoSQL database optimized for low-latency operations, but it is not suited for analytical workloads like those required for reporting.