Google Professional Data Engineer Question 118
Select 4Google Cloud PlatformYou are a Data Engineer at an organization that processes large volumes of data using Google Cloud's BigQuery. Your team is implementing a CI/CD pipeline for the SQL queries used in your data transformation workflows. Which steps should be included in the CI/CD pipeline to ensure high-quality and reliable deployments?
- A
Linting and static analysis of SQL queries to check for syntax errors and best practices
- B
Performing unit tests on SQL queries using a tool like dbt or custom scripts
- C
Directly deploying SQL queries to production without any testing to speed up the process
- D
Implementing version control for SQL scripts using a system like Git
- E
Running load tests to evaluate the performance of SQL queries under high data volume
- F
Skipping integration tests since SQL queries do not require them
Show answer and explanation
Correct answers: A, B, D, E
Explanation
A robust CI/CD pipeline for SQL-based data workflows should include linting, unit testing, version control, and load testing to ensure high-quality and reliable deployments. Skipping testing phases or directly deploying to production increases the likelihood of errors and system instability. By incorporating these steps, you can automate quality checks and ensure that your SQL queries meet performance and reliability expectations in production environments.
- A. Correct.
Linting and static analysis help catch syntax errors and enforce best practices, which is an essential step in the CI/CD process.
- B. Correct.
Unit tests ensure that individual SQL queries produce the expected results, which is crucial for maintaining data quality.
- C. Incorrect.
Directly deploying to production without testing introduces significant risk and is not a recommended practice.
- D. Correct.
Version control systems like Git allow you to track changes to SQL scripts, collaborate with other developers, and roll back to previous versions if needed.
- E. Correct.
Load testing helps ensure that your SQL queries perform well under realistic production workloads, which is critical for reliability.
- F. Incorrect.
Integration tests are important for validating that the SQL queries work well with other components in the pipeline, so skipping them is not advisable.