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| Section | Weight | Objectives |
|---|---|---|
| Implementing dbt Tests | 10% | - Built-in tests - Test configuration and execution - Custom tests |
| External Dependencies | 10% | - Using packages - Managing snapshots - External sources integration |
| Managing Data Pipelines | 15% | - Pipeline orchestration - CI/CD integration - Deployment strategies |
| Developing dbt Models | 20% | - Model design and structure
|
| Leveraging dbt State | 5% | - State management - State-aware operations |
| Debugging and Error Resolution | 15% | - Debugging techniques - Resolving data quality issues - Identifying modeling errors |
| dbt Models Governance | 15% | - Version control integration - Project organization and structure - Naming conventions and standards |
| Creating and Maintaining Documentation | 10% | - Generating documentation - Descriptions and metadata - Documentation standards |
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NEW QUESTION # 165
You're tasked with creating a model for audit purposes. The data must be preserved exactly as it was at a specific point in time. Update frequency is low, and there's no need for additional transformations on the captured dat a. What materialization should you use?
Answer: C
Explanation:
Snapshots are designed for historical preservation. They capture the state of a source at a moment in time, providing a perfect audit trail.
NEW QUESTION # 166
28. Consider this DAG:
* model_a # model_c # model_e
* model_b # model_d # model_f
(With model_c and model_d both feeding into the final layer.)
You execute:
dbt run --fail-fast
in production with 2 threads. During the run, model_b and model_c are running in parallel when model_b returns an error.
Assume there are no other errors in the model files, and model_c was still running when model_b failed.
Which model or models will successfully build as part of this dbt run? Choose 1 option.
Answer: B
Explanation:
The --fail-fast flag tells dbt to stop scheduling any new nodes as soon as one node fails. Importantly, dbt does not kill models that are already running; in-flight nodes are allowed to finish.
Here's what happens step by step with 2 threads:
* Roots model_a and model_b start first.
* model_a finishes successfully. That makes model_c eligible to run.
* dbt now runs model_b and model_c in parallel.
* While they are running, model_b fails.
* Because --fail-fast is set, dbt immediately stops scheduling any additional models (like model_d, model_e, or model_f).
* model_c was already running when model_b failed, so it is allowed to complete successfully.
Downstream models of either branch (model_d, model_e, and model_f) never start, because fail-fast prevents any further nodes from being queued after the first failure.
So, the only models that successfully build during this run are:
* model_a (completed before model_b failed)
* model_c (already running at the time of failure and allowed to finish) Hence the correct choice is B: model_a, model_c.
NEW QUESTION # 167
A model passes its tests during development, but later fails when deployed on a less powerful production database. Which of the following might be the reason for this discrepancy?
Answer: A,B
Explanation:
A and B could lead to tests passing in a forgiving environment but not catching issues in a more resource- constrained one. C would likely be caught earlier, and D is less likely
NEW QUESTION # 168
You've just added some schema tests to a critical model. Which command should you execute to ensure these new tests are run?
Answer: C
Explanation:
The dbt test command is specifically designed to execute the tests you've defined within your models.
NEW QUESTION # 169
Choose whether these scenarios describe a test or a contract:
Answer:
Explanation:
Explanation:
1. Can only be defined on SQL models
The Answer:
contract
2. Errors are returned before the model is built
The Answer:
contract
3. May be configured to customize severity
The Answer:
test
4. May be run on ephemeral models
The Answer:
test
dbt tests and contracts serve different purposes in ensuring data quality and model correctness.
Tests evaluate data after it is produced, while contracts validate the structure of a model before dbt attempts to build it.
A model contract is schema-level enforcement that describes required columns, data types, and constraints.
Contracts can only be applied to SQL models, not Python or ephemeral models. Because contracts validate the model's schema before executing any SQL, dbt surfaces those errors before the model is built, preventing invalid schemas from being deployed.
In contrast, tests evaluate the data after dbt builds a model. Tests can be written generically (unique, not_null, relationships, accepted_values) or as custom SQL tests.
They run after the model is materialized. Tests also allow severity configuration, enabling warnings instead of failures for less critical issues-something contracts do not support.
Tests also run on ephemeral models, because dbt expands ephemeral SQL inline within downstream models, allowing tests to still execute logically against the resulting compiled SQL. Contracts, however, do not apply because ephemeral models never materialize into database objects.
Thus:
* "SQL-only" and "errors before build" # contract
* "custom severity" and "run on ephemeral models" # test
If you want the next question formatted the same way, send it!
NEW QUESTION # 170
......
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