100%專業的dbt-Analytics-Engineering認證題庫，最好的考試資料幫助妳快速通過dbt-Analytics-Engineering考試KaoGuTi可以為你提供捷徑，給你節約好多時間和精力換。KaoGuTi會為你的dbt Labs dbt-Analytics-Engineering認證考試提供很好的培訓工具，有效的幫助你通過dbt Labs dbt-Analytics-Engineering認證考試。如果你在其他網站也看到了可以提供相關資料，你可以繼續往下看，你會發現其實資料主要來源於KaoGuTi，而且KaoGuTi提供的資料最全面，而且更新得最快。 最新的 Analytics Engineers dbt-Analytics-Engineering 免費考試真題 (Q84-Q89):問題 #84
You're implementing singular tests (accepted values). After providing a list of valid values, you notice some strange behavior: the test is passing even with records that contain unexpected dat a. What's the most likely issue?
A. A downstream process is overwriting the results after the model is built.
B. The model's data type isn't compatible with the accepted_values test.
C. The accepted_values test configuration has the wrong column specified.
D. Your test case is accidentally permitting null values, which bypass the check.
答案：B,C,D
解題說明：
Each of these directly impacts the accepted_values test's effectiveness, while D is unlikely for a singular test.
問題 #85
Which two are true about version controlling code with Git?
Choose 2 options.
A. Git prevents any sensitive fields from being saved in code.
B. All the code changes along the lifecycle of a project are tracked.
C. When bugs are raised, email notifications are automatically sent by Git to repository users.
D. Code can be reverted to a previous state.
E. Git automatically creates versions of files with suffixes.
答案：B,D
解題說明：
The correct answers are B: All the code changes along the lifecycle of a project are tracked, and E: Code can be reverted to a previous state.
Git is a distributed version control system designed to maintain a complete, chronological history of all code changes. Every commit records who made the change, when it occurred, and what the modification included.
This ensures transparency, reproducibility, and accountability across the development lifecycle, which makes B correct. Git also allows users to revert code to any previous commit, branch, or tag, making E correct as well. This capability is critical for recovering from mistakes, undoing faulty deployments, and ensuring stable releases.
Option A is incorrect because Git does not create file versions with suffixes; instead, it stores changes as snapshots within a repository. File suffixing is not part of Git's functionality.
Option C is incorrect because Git does not automatically send email notifications. Notification mechanisms come from hosting platforms like GitHub, GitLab, or Bitbucket-not from Git itself.
Option D is incorrect because Git does not prevent committing sensitive information. Developers must manually ensure secrets are excluded via .gitignore, secret managers, or pre-commit hooks. Git will store whatever is committed unless prevented through tooling.
Thus, only B and E correctly describe how Git supports version control in analytics engineering and dbt workflows.
問題 #86
You define several sources. However, some are frequently updated, while others rarely change. How can you optimize your dbt run command to account for this difference?
A. Employ the defer option if downstream models permit and ensure freshness checks are adjusted.
B. Include the -exclude flag along with less-frequently updated source names.
C. Group sources based on update frequency and create separate dbt run commands for each group.
D. Set up dbt schedules within your dbt_project.yml with different intervals for each group.
答案：C
解題說明：
Separating dbt run commands offers immediate control without using advanced features like schedules or deferring. The other options have merit in specific scenarios.
問題 #87
(Multiple Select)
A. Inserting large volumes of historical transactional data for backfilling purposes.
B. Defining generic tests that apply to multiple data sources.
C. Populating a lookup table with country codes.
D. Loading configuration data for production environments that differs from development settings.
答案：C,D
解題說明：
seeds are ideal for static reference data and environment-specific configurations. Large data backfills are usually handled outside of 'seeds'. Generic tests would be defined in the tests section.
問題 #88
You introduce performance optimizations to a subset of models. You need to benchmark both old and new versions in an isolated environment before deployment. How might you structure your dbt commands for this comparison?
A. Utilize dbt seed to populate separate datasets representing the old and new model outputs for side-by-side analysis.
B. Within a model, conditionally write to different schemas based on an environment variable, preserving both versions.
C. Use feature branches and switch between them with different dbt profiles for old and new code.
D. Add dbt hooks to temporarily archive the original output tables before overwriting them during benchmark runs.
答案：B,C
解題說明：
A facilitates testing versions in a clean way. D allows comparison within the database- B is for static data, not model outputs. C is less elegant, risking accidental data loss-