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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: dbt Models Governance	15%	- Project organization and structure - Version control integration - Naming conventions and standards
Topic 2: Debugging and Error Resolution	15%	- Resolving data quality issues - Identifying modeling errors - Debugging techniques
Topic 3: External Dependencies	10%	- Managing snapshots - External sources integration - Using packages
Topic 4: Creating and Maintaining Documentation	10%	- Descriptions and metadata - Documentation standards - Generating documentation
Topic 5: Managing Data Pipelines	15%	- CI/CD integration - Deployment strategies - Pipeline orchestration
Topic 6: Developing dbt Models	20%	- Model optimization 1. Model contracts 2. Performance tuning - Model design and structure 1. Incremental models 2. Materialization types 3. Ref and source functions
Topic 7: Implementing dbt Tests	10%	- Test configuration and execution - Custom tests - Built-in tests
Topic 8: Leveraging dbt State	5%	- State management - State-aware operations

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q214-Q219):

NEW QUESTION # 214
While onboarding a new team member, you need to ensure consistency between their local development setup and your existing production dbt deployment. Which of these are essential?

A. All of the above.
B. Providing clear documentation on configuration of profiles_yml to connect to the correct targets.
C. Enforcing version control and utilizing a requirements txt file to pin dbt and adapter dependencies.
D. Setting up access and permissions in the data warehouse for the new user, aligning with your team's security practices.

Answer: A

Explanation:
A: Version control and pinning dependencies ensure reliable behavior across machines. B: Accurate profiles are vital for successful dbt runs_ C: Data warehouse access is necessary for the developer to function.

NEW QUESTION # 215
You're ready to integrate your feature branch into the main branch. Which scenarios would necessitate a pull request and code review process?

A. You are working on a personal dbt project.
B. You are the only contributor to the dbt project.
C. You are working in a collaborative team environment with established quality control practices.
D. In all dbt projects, pull requests should be mandatory.

Answer: C,D

Explanation:
C: Code reviews are crucial in collaborative settings for improving quality and sharing knowledge. D: While not strictly mandatory always, pull requests are a best practice even when working alone as they encourage structured change tracking-

NEW QUESTION # 216
A sudden data quality issue occurs in production. You need to quickly reproduce the problem in a lower environment but retain a point-in-time snapshot of production dat a. Which strategies might you employ? Create a backup of the production database and restore it to a separate development or testing database.

A. A combination of the above, depending on time constraints and available resources.
B. Utilize data replication features (if supported by your data warehouse) to create a near real-time mirror of production data in a
C. staging area.
D. Use dbt snapshots to capture critical production tables during a defined timeframe for later use in troubleshooting.

Answer: A

Explanation:
A: Backups offer static point-in-time snapshots. B: Replication might be ideal for immediate mirroring, if available. C: Snapshots are lightweight yet can be time-sensitive.

NEW QUESTION # 217
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?

A. Schedule regular alerts whenever a test result deviates significantly from previous runs.
B. Automatically purge snapshots older than a certain date to save storage resources.
C. Convert the dbt test results and snapshots into time-series tables for easier trend analysis.
D. Integrate metadata about dbt model versions and schema changes alongside the snapshots.

Answer: A,C,D

Explanation:
These enhance the historical context and make the data actionable for resolving issues- A might discard valuable information prematurely

NEW QUESTION # 218
You're collaborating with a third-party analytics vendor who requires access to a subset of processed data within your dbt project for integration into their platform. How might you approach this securely?

A. A combination of the above might be needed, depending on the vendor's integration capabilities-
B. Set up a data sharing mechanism through your data warehouse, if it supports this functionality, enabling controlled access.
C. Generate a dedicated readout schema in your data warehouse with appropriate grants for the vendor's user
D. Utilize a dbt package to export specific models to CSV or JSON format and provide those files to the vendor

Answer: A

Explanation:
A: A separate schema isolates access and allows tailoring permissions. B: Data sharing features provide a secure and controlled channel. C: Offline extracts might be the only option for some vendors.

NEW QUESTION # 219
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