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Databricks Data Engineering Associate Exam, Exams of Advanced Education

Chamberlain College of NursingAdvanced Education

Databricks Data Engineering Associate Exam

Typology: Exams

2025/2026

Available from 03/17/2026

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DBT Analytics Engineering
Certification Exam-Graded A
Review the warehouse documentation.
To fix a Database Error, you should review the documentation of your data warehouse,
such as Snowflake or BigQuery docs, to debug the specific error.
Reference:https://docs.getdbt.com/guides/debug-errors? - ANSWER-What is the
recommended approach for fixing a Database Error?
1) Review the warehouse documentation
2) Rewrite all SQL queries
3) Delete the entire project
4) Start a new dbt project
The CI build stops and the failure is reported.
If a model fails during a CI build in dbt, the build stops, and the failure is reported,
preventing the faulty code from being merged into the main branch.
Reference:https://courses.getdbt.com/courses/take/advanced-deployment/texts/
39437556-review - ANSWER-In a dbt project, what happens if a model fails during a CI
build?
1) The model is automatically fixed by dbt
2) The CI build is considered successful
3) The CI build stops and the failure is reported
4) The model is excluded from future CI builds
It focuses on individual tasks without regard to others.
One-off jobs focus on individual tasks, possibly leading to redundant rebuilds.
Reference:https://courses.getdbt.com/courses/take/advanced-deployment/texts/
39437552-review - ANSWER-How does the one-off job approach differ from unified jobs
in dbt?
1) It builds the entire DAG every time.
2) It focuses on individual tasks without regard to others.
3) It only refreshes incremental models.
4) It uses a different set of dbt commands.
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DBT Analytics Engineering

Certification Exam-Graded A

Review the warehouse documentation. To fix a Database Error, you should review the documentation of your data warehouse, such as Snowflake or BigQuery docs, to debug the specific error. Reference:https://docs.getdbt.com/guides/debug-errors? - ANSWER-What is the recommended approach for fixing a Database Error?

  1. Review the warehouse documentation
  2. Rewrite all SQL queries
  3. Delete the entire project
  4. Start a new dbt project The CI build stops and the failure is reported. If a model fails during a CI build in dbt, the build stops, and the failure is reported, preventing the faulty code from being merged into the main branch. Reference:https://courses.getdbt.com/courses/take/advanced-deployment/texts/ 39437556-review - ANSWER-In a dbt project, what happens if a model fails during a CI build?
  5. The model is automatically fixed by dbt
  6. The CI build is considered successful
  7. The CI build stops and the failure is reported
  8. The model is excluded from future CI builds It focuses on individual tasks without regard to others. One-off jobs focus on individual tasks, possibly leading to redundant rebuilds. Reference:https://courses.getdbt.com/courses/take/advanced-deployment/texts/ 39437552-review - ANSWER-How does the one-off job approach differ from unified jobs in dbt?
  9. It builds the entire DAG every time.
  10. It focuses on individual tasks without regard to others.
  11. It only refreshes incremental models.
  12. It uses a different set of dbt commands.

Code blocks for configuring models. Macros are blocks of code that you can reuse multiple times. Reference:https://docs.getdbt.com/docs/build/projects - ANSWER-What are "macros" in the context of dbt projects?

  1. Code blocks for configuring models
  2. Blocks of code for bulk configurations
  3. Blocks of SQL queries
  4. Docs for your project WET. WET stands for "Write Everything Twice," implying code duplication. Reference:https://docs.getdbt.com/terms/dry - ANSWER-What is the opposite of DRY in software development?
  5. WET
  6. HARD
  7. SOFT
  8. DARE Include all columns. Snapshot source data in its raw form and include as many columns as possible, even if not immediately needed. Reference:https://docs.getdbt.com/docs/build/snapshots - ANSWER-What is the recommended approach for snapshotting source data in its raw form?
  9. Include all columns
  10. Apply business logic
  11. Use joins in the snapshot
  12. Select specific columns Writing singular tests. The recommended approach for testing multiple specific tables simultaneously is writing singular tests. Reference:https://docs.getdbt.com/best-practices/how-we-structure/6-the-rest-of-the- project - ANSWER-What is the recommended approach for testing multiple specific tables simultaneously in a dbt project?
  13. Writing singular tests
  14. Using generic tests
  15. Avoiding tests altogether
  1. Compiles SQL models
  2. Creates new models It uses a delete statement followed by an insert statement. On databases that do not support merge statements, dbt's incremental materialization uses a delete statement to delete records to be updated and then an insert statement. Reference:https://docs.getdbt.com/docs/build/incremental-models - ANSWER-How does dbt's incremental materialization work on databases that do not support merge statements?
  3. It uses a merge statement
  4. It uses a delete statement followed by an insert statement
  5. It uses an update statement
  6. It uses a truncate statement To avoid naming conflicts. Consistent file naming patterns help avoid naming conflicts and improve clarity. Reference:https://docs.getdbt.com/best-practices/how-we-structure/2-staging - ANSWER-Why should you use consistent file naming patterns in dbt staging models?
  7. To make the code look prettier
  8. To impress stakeholders
  9. To avoid naming conflicts
  10. To confuse data engineers When source data has millions or billions of rows. Incremental models are recommended when source data has millions or billions of rows for better query performance. Reference:https://docs.getdbt.com/docs/build/incremental-models - ANSWER-When is it recommended to use incremental models in dbt?
  11. When source data has millions or billions of rows
  12. When you want to create complex transformations
  13. When you want to skip transformations
  14. When you want to use regular tables Using the ref function. Seeds are referenced in downstream models by using the ref function. Reference:https://docs.getdbt.com/docs/build/seeds - ANSWER-How are seeds referenced in downstream models?
  15. Using the ref function
  16. Using SQL queries
  17. Using the seed command
  1. Using the seed file To view error details and logs. The primary purpose of using the Details tab in dbt Cloud IDE is to view error details and logs, which can help diagnose issues in your dbt project. Reference:https://docs.getdbt.com/guides/debug-errors? - ANSWER-What is the primary purpose of using the Details tab in dbt Cloud IDE?
  2. To create a snapshot of the project
  3. To execute SQL statements
  4. To view error details and logs
  5. To delete the compiled SQL files The custom database and the node being generated. The generate_database_name macro accepts two arguments: the custom database supplied in the model config and the node that a custom database is being generated for. Reference:https://docs.getdbt.com/docs/build/custom-databases - ANSWER-What arguments does the generate_database_name macro accept?
  6. The model name and the project name
  7. The custom database and the model node
  8. The custom database and the target node
  9. The custom database and the node being generated Query performance. Materialized view materializations offer the advantage of combining the query performance of a table with the data freshness of a view. Reference:https://docs.getdbt.com/docs/build/materializations - ANSWER-What is the key advantage of materialized view materializations in dbt compared to regular views?
  10. Data freshness
  11. Query performance
  12. Simplicity of use
  13. Manual refresh To name and describe data loaded into your warehouse. Sources in dbt are used to name and describe the data loaded into your warehouse, enhancing data lineage and testing. Reference:https://docs.getdbt.com/docs/build/sources - ANSWER-What is the primary purpose of using sources in dbt?
  14. To optimize query performance
  15. To document and test data transformations
  16. To name and describe data loaded into your warehouse
  17. To automate data loading processes 80 characters. Lines of YAML should be no longer than 80 characters. Reference:https://docs.getdbt.com/best-practices/how-we-style/5-how-we-style-our-
  • ANSWER-Which resource in a dbt project allows you to name and describe the data loaded into your warehouse?
  1. snapshots
  2. seeds
  3. sources
  4. metrics Use meaningful variable names. Examples of Jinja style: {{ this }} instead of {{this}}. Reference:https://docs.getdbt.com/best-practices/how-we-style/4-how-we-style-our-jinja
  • ANSWER-What should you do to improve the readability of Jinja code?
  1. Use meaningful variable names
  2. Use short and cryptic variable names
  3. Avoid using variables
  4. Use random variable names Basis for defining data. Semantic models serve as the basis for defining data in MetricFlow. Reference:https://docs.getdbt.com/docs/build/build-metrics-intro - ANSWER-What is the primary role of semantic models in MetricFlow?
  5. Basis for defining data
  6. Organizing YAML files
  7. Writing SQL queries
  8. Querying metrics Yes, and they can be configured to be hidden. Environment variables in dbt Cloud can include secrets and can be configured to be hidden from logs and the UI. Reference:https://courses.getdbt.com/courses/take/advanced-deployment/texts/ 39437558-review - ANSWER-Can environment variables in dbt Cloud contain secrets?
  9. No, they are always public
  10. Yes, but they are visible in the logs
  11. Yes, and they can be configured to be hidden
  12. They cannot include secrets due to security policies To restrict access to private models. A group is a collection of nodes within a dbt DAG. Groups are named, and every group has an owner. They enable intentional collaboration within and across teams by restricting access to private models. Reference:https://docs.getdbt.com/docs/build/groups - ANSWER-What is the purpose of dbt groups in a DAG?
  13. To restrict access to private models
  14. To organize models in folders
  15. To define model dependencies
  16. To schedule model runs All of the above.

MetricFlow allows you to develop from your preferred environment, whether that's the dbt Cloud CLI, dbt Cloud IDE, or dbt Core. Reference:https://docs.getdbt.com/docs/build/build-metrics-intro - ANSWER-In which environments can you develop with MetricFlow in dbt?

  1. dbt Cloud CLI
  2. dbt Cloud IDE
  3. dbt Core
  4. All of the above A library of dbt code. Packages are libraries that can be used in dbt projects. Reference:https://docs.getdbt.com/terms/dry - ANSWER-What is a dbt package?
  5. A storage container
  6. A cloud service
  7. A library of dbt code
  8. A user interface element Database connections. The profiles.yml file in dbt is used for managing database connections. Reference:https://docs.getdbt.com/dbt-cli/configure-your-profile - ANSWER-In dbt, what does the profiles.yml file manage?
  9. Model configurations
  10. Database connections
  11. Project dependencies
  12. Data sources Documentation for the project. The "docs" directory in a dbt project typically stores documentation for the project. Reference:https://docs.getdbt.com/docs/build/projects - ANSWER-What type of files are typically stored in the "docs" directory in a dbt project?
  13. Model definitions
  14. Project configuration files
  15. Documentation for the project
  16. Database schema descriptions When dealing with BigQuery. Materialized views are a suitable choice when incremental models are sufficient, but you want the data platform to manage the incremental logic and refresh. Reference:https://docs.getdbt.com/docs/build/materializations - ANSWER- When might you consider using materialized views instead of incremental models in dbt?
  17. For any use case
  18. For simple models
  19. When dealing with BigQuery
  20. When you need to manage incremental logic Specify dependencies for the exposure. Expected: depends_on: list of refable nodes, including ref, source, and metric (While possible, it is highly unlikely you will ever need
  1. To deploy models to different databases In dbt project yaml file and model sql file. Dbt project materialization can be chaged in dbt project yaml file and model sql file Reference:https://docs.getdbt.com/docs/build/materializations - ANSWER-How does dbt handle model materialization?
  2. Only in dbt project yaml file
  3. Only in model sql file
  4. In dbt project yaml file and model sql file
  5. Does not handle at all Yes, simultaneously with multiple configurations. dbt can be used with multiple data warehouses simultaneously, each with its configuration. Reference:https://docs.getdbt.com/docs/available-adapters - ANSWER-Can dbt be used with multiple data warehouses?
  6. Yes, but only sequentially
  7. No, it is limited to one at a time
  8. Yes, simultaneously with multiple configurations
  9. It does not support data warehouses In the referenced SQL file. Start by opening the SQL file where the error occurs Reference:https://docs.getdbt.com/guides/debug-errors? - ANSWER-Where should you start debugging an "Invalid ref function" error in dbt?
  10. In the dbt_project.yml file
  11. In the profiles.yml file
  12. In the referenced SQL file
  13. In the dbt logs Custom alias and node name. The generate_alias_name macro accepts the custom alias supplied in the model config and the node for which it's generated. Reference:https://docs.getdbt.com/docs/build/custom-aliases - ANSWER-What does the generate_alias_name macro accept as arguments?
  14. Node and node version
  15. Model name and alias name
  16. Model config and node name
  17. Custom alias and node name Descriptions. You can also add descriptions to sources, that get rendered as part of your documentation site. Reference:https://docs.getdbt.com/docs/build/sources - ANSWER-What can you add to sources in DBT for documentation purposes?
  18. Descriptions
  19. Filters
  20. Constraints
  21. Data tests

Use 'dbt remove' command. You can remove deleted models from your data warehouse using the 'dbt remove' command. Reference:https://docs.getdbt.com/docs/build/sql- models - ANSWER-How can you remove deleted models from your data warehouse using dbt?

  1. Use 'dbt remove' command
  2. Delete the model files
  3. Use 'dbt drop' command
  4. Use 'dbt refresh' command The old row is updated with the new row. When the same unique key is present in both old and new model data, dbt updates/replace the old row with the new row of data. Reference:https://docs.getdbt.com/docs/build/incremental-models - ANSWER-What happens when the same unique key is present in both old and new model data in an incremental model?
  5. The old row is updated with the new row
  6. The old row is deleted
  7. The new row is appended
  8. An error occurs Isolating complex operations. Intermediate models are commonly used for isolating complex operations and making them easier to refine and troubleshoot. Reference:https://docs.getdbt.com/best-practices/how-we-structure/3-intermediate - ANSWER-What are some common use cases of intermediate models?
  9. Materialization as tables
  10. Isolating complex operations
  11. Exposing to end users
  12. Focusing on single entities To identify the type of error. The error message dbt produces contains the type of error and the file where the error occurred. Reference:https://docs.getdbt.com/guides/debug- errors? - ANSWER-What is the primary purpose of reading error messages in dbt?
  13. To find the line number of the error
  14. To identify the type of error
  15. To determine the user who caused it
  16. To see the error in the logs Runs CI jobs in parallel. CI jobs are handled differently and execute concurrently in parallel to increase productivity and avoid blocking production runs.(https://docs.getdbt.com/docs/deploy/job-scheduler) Reference:https://docs.getdbt.com/docs/deploy/job-scheduler - ANSWER-How does the scheduler handle CI (continuous integration) jobs?
  17. Runs CI jobs in parallel
  18. Runs CI jobs in serial
  19. Gives CI jobs higher priority
  20. Requires additional slots