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| Section | Weight | Objectives |
|---|---|---|
| Implementing dbt Tests | 10% | - Test configuration and execution - Custom tests - Built-in tests |
| Creating and Maintaining Documentation | 10% | - Generating documentation - Documentation standards - Descriptions and metadata |
| dbt Models Governance | 15% | - Naming conventions and standards - Project organization and structure - Version control integration |
| Developing dbt Models | 20% | - Model design and structure
|
| Debugging and Error Resolution | 15% | - Identifying modeling errors - Resolving data quality issues - Debugging techniques |
| Leveraging dbt State | 5% | - State-aware operations - State management |
| Managing Data Pipelines | 15% | - Pipeline orchestration - Deployment strategies - CI/CD integration |
| External Dependencies | 10% | - Using packages - External sources integration - Managing snapshots |
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NEW QUESTION # 317
You are building an incremental model.
Identify the circumstances in which is_incremental() would evaluate to True or False.
Answer:
Explanation:
Explanation:
1. There is a config block at the top of the model with materialized = 'table'
## Answer: False
2. The corresponding table already exists in the data warehouse
## Answer: True
3. The incremental model was executed with the --full-refresh flag
## Answer: False
4. The corresponding table does not already exist in the data warehouse
## Answer: False
The is_incremental() macro in dbt is used within an incremental model to determine whether the current invocation should perform an incremental update or a full rebuild. It evaluates to True only during an incremental run when the target table already exists in the data warehouse and dbt is not performing a full refresh.
For is_incremental() to return True, two conditions must be met:
* The model must be materialized as incremental, not table or view.Therefore, if the config specifies materialized = 'table', the model is not incremental, and the function evaluates to False.
* The table already exists in the target schema.In this case, dbt will run the model in incremental mode, making is_incremental() return **True`.
If the incremental model is run with --full-refresh, dbt intentionally rebuilds the entire table, meaning is_incremental() evaluates to False, even if the table exists.
Lastly, if the target table does not exist yet, dbt must create it from scratch, so the run is treated as a full rebuild, not an incremental update, causing is_incremental() to evaluate to False.
Thus, the only scenario where is_incremental() returns True is when the table exists and the model is actually incremental.
NEW QUESTION # 318
You've implemented the built-in dbt.get_column_values macro to display sample data values from a source column directly on the DAG. However, you notice performance issues when loading the docs. Which optimization strategy could you consider?
Answer: B,C,D
Explanation:
B: Disabling expensive computations conditionally can boost performance for production environments. C: Snapshots pre-compute values, potentially improving DAG loading times. D: Reducing the amount of data retrieved by the macro could help with performance.
NEW QUESTION # 319
You have a dbt macro that generates a list of models to execute dynamically. Which dbt command should you use in conjunction with this macro to actually run those models?
Answer: D
Explanation:
A makes the dbt graph available, including macros, during execution- B gets metadata, but not for execution. C helps troubleshoot, but not run macros. D isn't designed for dynamic macro output
NEW QUESTION # 320
After adding several new models to your project, you want to execute only those models and their direct dependencies. Which command combination best achieves this?
Answer: D
Explanation:
The + syntax with dbt run allows you to specify models and their upstream dependencies. Dbt build encompasses run and test along with snapshot execution.
NEW QUESTION # 321
(Multiple Select)
Answer: A,B,C,D
Explanation:
Each of these provides some level of tracking:A for dbt project changes. B at the database level (if the feature exists). C for comprehensive lineage insights. D for a granular view of dbt activity.
NEW QUESTION # 322
......
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