You implement dbt tests to monitor data quality over time. Which of the following scenarios could these tests potentially help you detect?

• A.Gradual degradation in source data completeness due to an API rate limit being reached
• B.Performance issues in your data warehouse impacting the speed of dbt model updates.
• C.An accidental schema change by someone working outside of your dbt project-
• D.An unexpected spike in web traffic leading to invalid data entries in your source system-

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Examine how freshness is defined at the database level:
- name: raw
database: raw
freshness: # default freshness
warn_after: {count: 12, period: hour}
error_after: {count: 24, period: hour}
loaded_at_field: _etl_loaded_at
How can one table from the source raw be excluded from source freshness?

• A.Add freshness: null to the table configuration.
• B.Since freshness is defined at the source level, all tables in the source must adhere to the freshness parameters.
• C.Add loaded_at_field: null to the table configuration.
• D.Add error_after: null to the table configuration.

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You introduce a minor formatting change to a large SQL model. Afterwards, the results change unexpectedly. Which dbt-related issue might explain this, even if the SQL itself appears correct?

• A.A subtle indentation change in a CTE accidentally modifies the execution order within the query.
• B.You've used a reserved keyword as a column alias without properly quoting it.
• C.There's a version mismatch between the dbt library used during development and in production.
• D.An upstream data issue only surfaces due to the formatting change making that part of the query execute differently.

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(Multiple Select)

• A.Refer to the dbt documentation for a comprehensive list of valid properties within schema files.
• B.Utilize a YAML validator tool independently of dbt to check for general formatting errors.
• C.If available, compare your schema.yml to a previous working version to spot problematic changes.
• D.Introduce a global persist_docs setting within your dbt_project.yml file to resolve schema inconsistencies.

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