Google Professional Data Engineer Question 122
Single answerGoogle Cloud PlatformYour company collects IoT data from thousands of sensors deployed across multiple locations. The data must be ingested and stored in a way that enables low-latency querying for real-time dashboards, as well as batch processing for analytics. The data is semi-structured, and the solution must scale with minimal operational overhead. Which Google Cloud storage solution should you choose?
- A
Cloud Bigtable
- B
Cloud SQL
- C
Cloud Storage
- D
BigQuery
Show answer and explanation
Correct answer: A
Explanation
The requirement to support low-latency queries for real-time dashboards and handle semi-structured data makes Cloud Bigtable the best choice. It is built for high-throughput, low-latency workloads and can scale horizontally with minimal operational overhead. While other options like BigQuery and Cloud Storage are excellent for analytics and storage, they do not fulfill the real-time querying requirement effectively.
- A. Correct.
Cloud Bigtable is designed for low-latency access to large volumes of semi-structured data, making it suitable for the described use case. It scales seamlessly and is fully managed, reducing operational overhead.
- B. Incorrect.
Cloud SQL is suitable for structured data and transactional use cases but is not ideal for low-latency querying of large-scale semi-structured data.
- C. Incorrect.
Cloud Storage is a great choice for unstructured data and batch processing, but it does not provide the low-latency querying capabilities required for real-time dashboards.
- D. Incorrect.
BigQuery is optimized for large-scale analytics and batch processing rather than low-latency real-time use cases, making it less suitable for this scenario.