dbt Labs dbt Analytics Engineering Certification : dbt-Analytics-Engineering

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dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. Your development environment uses a smaller, sampled dataset compared to production for efficiency. When a new performance-sensitive model is deployed, users report significant slowdowns. What might be some of the potential causes?

A) The smaller dataset in development didn't reveal performance issues that become apparent at the scale of production data
B) Performance optimizations made in development might not translate directly to the larger production data volumes.
C) All of the above-
D) Your data warehouse might have different resource configurations or indexing in the production environment.

2. You need to run a dbt job that performs a long-running data cleansing operation. The job occasionally times out. Which of the following are potential solutions?

A) Schedule the job to run concurrently with other dbt models to maximize resource usage-
B) Break the cleansing logic into multiple models, chaining them with dependencies-
C) Increase the timeout setting in your CI/CD tool or dbt job configuration.
D) Use a dbt macro to retry the cleansing operation with a backoff strategy within the model itself-

3. You discover a model sorting large amounts of data using an ORDER BY clause with several columns. Performance needs to be increased. What's the FIRST step in your optimization process?

A) Examine query execution plans to identify bottlenecks and potential index usage.
B) Change the materialization from a 'table' to a 'view'.
C) Add a LIMIT clause to restrict the number of records sorted.
D) Remove unnecessary columns from the ORDER BY clause.

4. A new feature you're developing requires significant changes across multiple models in your dbt project. Which branching strategy would be the most suitable and why?

A) Work directly on the main branch, as it ensures your changes are always up-to-date.
B) Create a feature branch for the new development to isolate your work.
C) Avoid using branches altogether, as they can introduce unnecessary complexity into a dbt workflow
D) Create separate branches for each model you'll be modifying to minimize conflicts.

5. You receive a compilation error stating:Model depends on a node named 'ref data' which was not found

A) Review downstream models that might be referencing ref_data incorrectly.
B) Search for a model named ref_data within your project or any included packages.
C) Check the configuration of the ref_data data source.
D) Examine the SQL within the model where the error occurs for typos or incorrect ref() usage.

Solutions: