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| Section | Objectives |
|---|---|
| dbt Core Concepts | - Models and materializations
|
| Deployment and Orchestration | - Environments and workflows
|
| Documentation and Lineage | - Data lineage understanding
|
| Analytics Engineering Foundations | - SQL proficiency for analytics
|
| Testing and Data Quality | - Built-in and custom tests
|
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NEW QUESTION # 12
You establish a process using dbt tests and snapshots to track data quality changes over time. To maximize the utility of this historical record for troubleshooting, what additional step would be beneficial?
Answer: A,B,D
Explanation:
These enhance the historical context and make the data actionable for resolving issues- A might discard valuable information prematurely
NEW QUESTION # 13
Which of the following is true about restricting the usage of models in dbt?
Choose 1 option.
Answer: A
Explanation:
The correct answer is C: Model groups can limit references by other models which aren't in the same group.
According to the dbt documentation, dbt provides a formal access-control mechanism for models through model groups and the access property. Models can be assigned to groups, and each model can be marked as public, protected, or private. The purpose of this system is to create clear boundaries within a project, making it possible to control which models are allowed to reference others. Specifically, dbt enforces rules where models in a group can restrict references from models outside that group, which helps maintain modularity and prevents accidental coupling of unrelated data layers. This is extremely valuable in large analytics engineering projects where teams manage different domains or data products.
Option A is incorrect because dbt does not use Git user groups or any form of identity-based access control for model usage. Option B is incorrect because dbt does not integrate with warehouse roles for controlling model references-access is handled strictly within the dbt project's metadata. Option D is incorrect because user emails or platform identities have no role in determining which models can reference others. dbt enforces usage rules only through its metadata-driven grouping and access configuration system.
NEW QUESTION # 14
A new dataset is loaded into your warehouse as a table daily. You need to create a dbt source for it. Which is the MOST essential element to include in your configuration?
Answer: B
Explanation:
At a minimum, dbt needs to know where to find this source table. Freshness checks and others are valuable but not strictly required for the source to function.
NEW QUESTION # 15
Which explanation describes how dbt infers dependencies between models?
Choose 1 option.
Answer: C
Explanation:
The correct answer is A: Information is gathered from the use of source and ref macros.
dbt determines the dependency graph - the DAG - by analyzing calls to ref() and source() inside model SQL files. These macros explicitly declare relationships between models. When a developer writes ref ('orders'), dbt interprets this as: "the current model depends on the orders model." Similarly, source() indicates dependencies on upstream raw data sources. This declarative approach allows dbt to build a structured and deterministic DAG without scanning SQL for implicit table references.
Option B is incorrect because dbt does not query database objects to infer dependencies; it resolves dependencies at compile time through metadata generated from model files. Option C is incorrect because dbt intentionally does not parse SQL to detect table names-this would be brittle and error-prone across warehouses. Instead, dbt requires explicit references to maintain reliability. Option D is incorrect because YAML files define metadata about models and sources but do not create dependency relationships between them.
Thus, the dependency graph is built exclusively by reading ref() and source() macro calls, which ensures clarity, correctness, and maintainability within the analytics engineering workflow.
NEW QUESTION # 16
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 # 17
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