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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. You create tests to validate counts and timestamps against a baseline dataset. The tests fail unexpectedly. What might be possible root causes?

A) The baseline dataset itself has become corrupted
B) There are differences in data types or time zone handling between the model and baseline.
C) Your tests are too strict and need more generous tolerances.
D) Your upstream ETL process has a logic error, leading to incorrect data.

2. (Multiple Select)

A) IJse the -select flag with dbt run to execute models incrementally, starting with the most upstream dependency.
B) Add -full-refresh flag to dbt run to ensure all models are rebuilt from scratch.
C) Write custom macros to log intermediate data for each model.
D) Run dbt docs generate and dbt docs serve to inspect the lineage graph.

3. A pull request includes changes to both dbt models and configuration files in your dbt_project.yml file. During the merge, conflicts arise in the configuration file. How would you approach resolving these conflicts?

A) Request a separate, smaller pull request dedicated to the configuration changes to isolate the conflict.
B) Utilize Git's merge conflict markers to carefully combine changes in the configuration file.
C) Ask the author of the pull request to rebase their changes and resolve the configuration conflict in their branch.
D) Give priority to the model changes and manually edit the configuration file after.

4. You have a dbt model that depends on several upstream source tables. One of these source tables is occasionally updated very late, causing your job to fail if triggered at the usual time. What configuration could mitigate this?

A) Redesign the model with an incremental materialization strategy that gracefully handles partial updates.
B) Configure a dbt hook to run before the job, dynamically checking freshness of the source table.
C) Set the -full-refresh flag for the dbt job to ensure all tables are materialized.
D) Add a depends_on relationship pointing to the potentially late table within your model.

5. You're setting up baseline comparisons with historical dat
a. Which factors are crucial to consider when selecting or generating the baseline dataset?

A) If using data, the baseline might need sanitization to remove PII-
B) The baseline needs to align in structure (schemas) with the dbt models being tested.
C) The baseline should cover a representative time range relevant to your analysis.
D) The data volume in the baseline should be large enough to identify statistical patterns.

Solutions: