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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: dbt Fundamentals | 15% | - dbt workflow and best practices - dbt project structure - dbt Core vs dbt Cloud |
| Topic 2: Data Transformation Techniques | 25% | - Refactoring and incremental models - Jinja templating - Macros and packages - Common table expressions and subqueries |
| Topic 3: Deployment and Orchestration | 15% | - CI/CD with dbt Cloud - Jobs and scheduling in dbt Cloud - Git version control integration - Environments (dev, staging, prod) |
| Topic 4: Models | 25% | - Materializations (table, view, ephemeral, incremental) - Writing and managing SQL models - Snapshots - Sources and references - Seeds |
| Topic 5: Testing and Documentation | 20% | - dbt docs and DAG visualization - Schema tests (unique, not_null, accepted_values, relationships) - Documentation generation - Custom data tests |
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NEW QUESTION # 236
You discover that a heavily used model is taking significantly longer to materialize. After investigation, you determine that the complexity of the model's logic is a contributing factor. Which of the following actions is LEAST likely to help improve performance?
Answer: C
Explanation:
Switching from a table to a view alone doesn't address the core performance issue of complex logic. Other options prioritize breaking down the transformations or directly optimizing the SQL itself.
NEW QUESTION # 237
You have written this new agg_completed_tasks dbt model:
with tasks as (
select * from {{ ref('stg_tasks') }}
)
select
user_id,
{% for task in tasks %}
sum(
case
when task_name = '{{ task }}' and state = 'completed'
then 1
else 0
end
) as {{ task }}_completed
{% endfor %}
from tasks
group by 1
The dbt model compiles to:
with tasks as (
select * from analytics.dbt_user.stg_tasks
)
select
user_id,
from tasks
group by 1
The case when statement did not populate in the compiled SQL. Why?
Answer: C
Explanation:
In dbt, Jinja runs at compile time and operates only on Python objects that exist in the Jinja context (variables, lists, dictionaries, etc.). The tasks inside your with clause:
with tasks as (
select * from {{ ref('stg_tasks') }}
)
defines a SQL CTE named tasks, not a Jinja variable. Jinja cannot iterate over a SQL CTE; it can only loop over a Python iterable that has been created or passed into the template. Because there is no Jinja variable named tasks defined with something like:
{% set tasks = ['task_a', 'task_b', 'task_c'] %}
the for task in tasks loop has nothing to iterate over. As a result, the entire loop body is effectively skipped during compilation, and the compiled SQL only contains:
select
user_id,
with no generated case when expressions.
Option A is incorrect because loop.last is only needed for formatting (e.g., commas), not for the loop to render. Option B is wrong because Jinja control structures correctly use {% %}, while {{ }} is for output.
Option D is irrelevant to compilation; missing columns would cause a runtime database error, not an empty compiled block.
Therefore, the problem is that no Jinja variable tasks was defined, making C the correct answer.
NEW QUESTION # 238
A colleague expresses confusion about how dbt uses the dbt_project.yml file. Which of the following is the MOST accurate high-level explanation?
Answer: D
Explanation:
Emphasize the configuration aspect of dbt_project.yml; it guides dbt's behavior but doesn't contain the SQL logic itself.
NEW QUESTION # 239
You define a new generic test on model customers in a YAML file:
version: 2
models:
- name: customers
columns:
- name: customer_id
tests:
- unique
- not_null
The next time your project compiles you get this error:
Raw Error:
mapping values are not allowed in this context
in "<unicode string>", line 7, column 21
What is the cause of this error?
Answer: C
Explanation:
This error occurs because the YAML structure is incorrectly indented, causing dbt's parser (and YAML itself) to misinterpret the test definitions. In dbt, generic tests must be declared as a list under the tests: key, but YAML is extremely sensitive to indentation levels. In the faulty YAML, unique and not_null are indented incorrectly relative to the tests: key, which produces the error: "mapping values are not allowed in this context." According to the dbt Testing documentation, valid generic test syntax follows this exact pattern:
columns:
- name: id
tests:
- unique
- not_null
The indentation under tests: must be consistent and aligned so that YAML interprets the items as list elements, not as malformed mappings. When indentation is wrong, YAML attempts to parse list entries as key-value mappings, which leads to the error seen during compilation.
dbt does not require generic test names to be quoted, nor does it expect tests to be a dictionary. The test list format is correct-only the indentation is wrong. Therefore, the root cause is incorrect YAML indentation, making Option D correct.
NEW QUESTION # 240
Which two are true about dbt tests?
Choose 2 options.
Answer: B,C
Explanation:
The correct answers are C and D.
dbt supports two main categories of tests: generic tests and singular tests. Generic tests are defined in YAML and applied to models or columns, while singular tests are written as SQL files placed in the /tests/ directory.
This makes Option C correct-singular tests must be created as .sql files inside that folder, and dbt will execute each file as a test query.
Option D is also correct. dbt includes four built-in generic tests: unique, not_null, relationships, and accepted_values. These are considered "native" tests and are available without requiring any additional packages. They cover the most common data quality checks and are applied through YAML configurations on models or columns.
Option A is incorrect because dbt does not automatically apply any tests. All tests-native or custom-must be explicitly defined in YAML or created manually. Nothing is inferred from primary keys.
Option B is incorrect because dbt's package hub contains community packages, not the list of native tests.
Native tests are documented directly within dbt's core functionality.
Option E is incorrect because the constraints configuration is used to create database-level constraints on supported warehouses, not to run dbt tests. Tests still require YAML test definitions or .sql files.
Thus, only C and D accurately describe dbt's testing behavior.
NEW QUESTION # 241
......
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