Google Professional Data Engineer Question 133
Single answerGoogle Cloud PlatformYour company is designing a data pipeline for processing large quantities of IoT data. The data needs to be ingested in real-time, but will only be queried occasionally for analytics purposes. The company wants to minimize storage costs while ensuring acceptable performance for querying. Which storage solution should you recommend?
- A
Cloud Bigtable
- B
BigQuery
- C
Cloud Storage with lifecycle policies
- D
Cloud SQL
Show answer and explanation
Correct answer: C
Explanation
Cloud Storage with lifecycle policies is the best choice for this scenario as it minimizes storage costs by automatically transitioning data to lower-cost storage classes while still providing the ability to query data occasionally, such as by using tools like BigQuery or Dataflow. This approach balances cost-efficiency with adequate performance for infrequent analytics use cases.
- A. Incorrect.
Cloud Bigtable is optimized for low-latency, real-time analytics but is not cost-effective for occasional queries, especially when the data is not accessed frequently.
- B. Incorrect.
BigQuery is designed for analytical queries but can be more expensive for large datasets that are not queried frequently.
- C. Correct.
Cloud Storage with lifecycle policies is the most cost-effective option for storing large amounts of data that is infrequently accessed but still allows for acceptable performance for analytics use cases when combined with appropriate querying tools.
- D. Incorrect.
Cloud SQL is designed for transactional workloads and relational data, which doesn't align with the requirements of large-scale IoT data storage and occasional queries.