Google Professional Data Engineer Question 155
Select 3Google Cloud PlatformYour organization is building a data lake on Google Cloud to store massive amounts of structured and unstructured data. The data lake will serve as a foundation for analytics and machine learning workloads. Which of the following are important considerations when designing this data lake?
- A
Ensuring data is stored in a cost-effective storage tier, such as Google Cloud Storage Nearline or Coldline, based on access patterns
- B
Implementing fine-grained IAM permissions on the data lake to secure access to sensitive data
- C
Storing all data in a single format, such as CSV, to simplify data processing and analytics
- D
Designing a zone-based architecture with raw, processed, and curated data layers to organize and manage data effectively
- E
Configuring Cloud SQL as the primary storage backend to manage the raw data in the data lake
Show answer and explanation
Correct answers: A, B, D
Explanation
When designing a data lake on Google Cloud, it is important to consider storage cost optimization, security through fine-grained IAM permissions, and best practices such as a zone-based architecture for efficient data organization. Using appropriate storage solutions (e.g., Google Cloud Storage) and supporting multiple data formats are also crucial for maintaining flexibility and scalability in data lake design.
- A. Correct.
Correct: Selecting cost-effective storage tiers like Nearline or Coldline for infrequently accessed data is critical for optimizing costs while maintaining accessibility.
- B. Correct.
Correct: Fine-grained IAM permissions are essential for ensuring that only authorized users and services can access sensitive data in the data lake.
- C. Incorrect.
Incorrect: Storing all data in a single format limits flexibility and compatibility with different analytics tools. Data lakes are designed to accommodate various formats, such as JSON, Parquet, Avro, or CSV.
- D. Correct.
Correct: A zone-based architecture (e.g., raw, processed, curated) is a best practice for organizing data in a data lake. It ensures better data governance, lineage, and usability.
- E. Incorrect.
Incorrect: Cloud SQL is a relational database service that is not designed to serve as the primary storage backend for a data lake. Google Cloud Storage is the preferred option for data lake storage.