最新のdbt-Analytics-Engineering問題集で試験を準備する

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dbt Labs dbt Analytics Engineering Certification 認定 dbt-Analytics-Engineering 試験問題：

問題 #1

You're working on a dbt project in a development environment where compute resources are limited. You want to prototype a new model quickly without incurring high materialization overhead. Which materialization would be most suitable for this?

A. Ephemeral
B. Incremental
C. Snapshot
D. Table

問題 #2

You have a time-sensitive incremental model that must run as quickly as possible whenever new data arrives. What dbt feature or configuration might be crucial for optimization?

A. Configure the model to run with maximum possible concurrency.
B. Set the model to refresh on a frequent, time-based schedule.
C. Define appropriate materializations (table, view, incremental) for the model.
D. Use the dbt run -select flag to execute only that specific model.

問題 #3

A model refactors a frequently used SQL calculation. Traditionally this logic was copied across multiple models. Which of the following is the LEAST likely benefit of refactoring this calculation into a macro?

A. Faster dbt job execution time
B. Simplified dependency tracking
C. Reduced error potential due to a single source of logic
D. Improved readability of models

問題 #4

During development, you frequently used temporary print statements for debugging. Which of the following is the best practice before opening a pull request?

A. Leave the print statements for future reference, in case similar debugging is needed-
B. Comment out the print statements but leave them in the code.
C. Consolidate the print statements into a separate debugging function that can be toggled on and off
D. Remove the print statements entirely from your commits-

問題 #5

(Multiple Select)

A. The staging model run will fail.
B. dbt will issue a warning but continue processing.
C. Downstream models relying on the staging model will continue to function.
D. The dbt run will succeed, but the staging model will have null values due to the missing data.

解説：