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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q114-Q119):

NEW QUESTION # 114
You've identified the same complex date calculations repeated across multiple models. Which approach aligns with modularity and DRY (Don't Repeat Yourself) principles?

A. Introduce a new intermediate table to store the result of the date calculations.
B. Create a macro, encapsulating the date calculations, and reference it in the affected models.
C. Continue copying the date calculation logic into each relevant model.
D. Write a custom Python function and import it into your dbt project.

Answer: B

Explanation:
Macros excel in encapsulating reusable logic, promoting modularity and avoiding code repetition. While option C could work, it introduces unnecessary materialization.

NEW QUESTION # 115
Which of the following scenarios might warrant a git rebase instead of a standard git merge when integrating your changes into the main branch?

A. You want to avoid a merge commit and keep a linear project history.
B. Your branch has diverged significantly from the main branch with unrelated changes.
C. You only want to include a subset of your feature branch commits in the main branch.
D. You need to resolve complex merge conflicts that arise during a standard merge.

Answer: A,B

Explanation:
A Rebasing creates a more linear history, making it easier to trace changes over time. D. Rebasing allows for a cleaner integration when a feature branch contains intermingled changes that shouldn't all be merged.

NEW QUESTION # 116
"Our dbt jobs take hours to run, and it's hard to know why!" says a frustrated colleague. What initial investigation steps would you suggest?

A. Look into dbt's profiling capabilities to pinpoint the slowest models and queries.
B. Check your dbt_project.yml configuration for any project-wide performance settings to optimize.
C. Review any 'on-run-start' or 'on-run-end' hooks that might add unexpected overhead.
D. All of the above.

Answer: C

Explanation:
Each of these could provide valuable insights. Start with profiling to find the most performance-critical areas, but don't neglect hooks and potential config-level optimizations.

NEW QUESTION # 117
Your fct_orders model depends on both raw_sales and stg_customers. Due to upstream changes, the customer_id column in raw_sales is now named cust_id. How could you manage this change with minimal disruption?

A. Create an alias for customer_id as cust_id in the stg_customers model.
B. Utilize dbt's ref() function to dynamically adapt to the new column name.
C. Use a dbt source to rename the column in raw sales.
D. Update the fct_orders model to reference cust_id.

Answer: B

Explanation:
The ref() function is designed for these situations. It makes your models adaptable to upstream changes. Option A would work but creates maintenance overhead.

NEW QUESTION # 118
Your dbt project is part of a larger application where code for multiple components is merged into a shared main branch. Conflicts are becoming frequent. Which strategies could help mitigate merge conflicts?

A. All of the above.
B. Encourage frequent merging of smaller feature branches into the main branch.
C. Develop a communication process to notify teammates when changes are made to potentially shared models or sources.
D. Establish clear ownership and responsibilities for different areas of the dbt project.

Answer: A

Explanation:
Explanation: A Clear ownership reduces the likelihood of conflicting edits. B: Proactive communication helps avoid surprise changes that can cause conflicts_ C: Smaller changesets decrease the potential for conflicting changes across branches.

NEW QUESTION # 119
......

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