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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

dbt Labs dbt Analytics Engineering Certification Sample Questions:

Question 1

"Sometimes columns that should have data are showing null values!" exclaims a colleague. What initial debugging steps would you suggest beyond examining the model logic itself?

A. Review if there are snapshots or merge strategies that might impact how the table is updated.
B. All of the above.
C. Check any recent changes to source definitions or transformations on upstream data.
D. Verify that any where clauses or filters in the model are not inadvertently too restrictive.

Question 2

You need to give read-only access to a specific dataset in your production data warehouse to a data analyst on your team. How might you approach this using dbt environments?

A. Use row-level security features in your data warehouse and dynamically filter data in models using environment variables.
B. Modify the data warehouse permissions directly to grant access to the required dataset.
C. A combination of the above, depending on the capabilities of your data warehouse.
D. Create a dedicated dbt target for the analyst and utilize grants within your models to control access.

Question 3

(Multiple Select)

A. Leveraging appropriate indexes on columns used in joins and WHERE clauses.
B. Using SELECT * whenever possible to avoid explicitly specifying needed columns.
C. Preferring correlated subqueries over joins when relationships are one-to-one.
D. Avoiding excessive use of UNION operations, especially within loops.

Question 4

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

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

Question 5

Collaborative Fix

A. Include updated model documentation (dbt docs) outlining the logic and reasons for adjustment.
B. Add clear commit messages that concisely summarize the purpose of the fix.
C. All of the above.
D. Open a pull request with detailed comments explaining the rationale for the changes and any potential side-effects.

Solutions: