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dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. dbt Model Snippet:SQL

A) Ensuring the grains variable is defined in dbt_project.yml or a macro.
B) Checking that the date_part() function is compatible with your database-
C) Validating that the column names generated by the Jinja loop would be valid SQL identifiers.
D) Making sure the source table fct_orders contains the expected columns.

2. You've been tasked with improving the discoverability of dbt models within your project. Which of the following changes would be the MOST effective in achieving this goal?

A) Using custom macros to dynamically generate model descriptions based on metadata.
B) Writing longer, more verbose descriptions for each column in your models.
C) Adding a tags list to all models, even if the tags are somewhat generic.
D) Ensuring models have clear and concise descriptions that accurately reflect their purpose.

3. (Multiple Select)

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

4. You're working with ephemeral models in your dbt project. Which scenarios could cause an ephemeral model to fail?

A) A downstream dependency of the ephemeral model fails.
B) Data quality tests defined within the model are not met.
C) An upstream source table is temporarily inaccessible.
D) A syntax error in the model's SQL code.

5. (Multiple Select)

A) Tables intended to be empty as part of a process truly have zero records.
B) Foreign key relationships are consistently enforced.
C) Columns intended to contain timestamps actually store valid timestamp values.

Solutions: