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| Section | Weight | Objectives |
|---|
| Topic 1: Testing and Documentation | 20% | - Custom data tests - dbt docs and DAG visualization - Documentation generation - Schema tests (unique, not_null, accepted_values, relationships)
|
| Topic 2: Models | 25% | - Snapshots - Sources and references - Materializations (table, view, ephemeral, incremental) - Seeds - Writing and managing SQL models
|
| Topic 3: Deployment and Orchestration | 15% | - Jobs and scheduling in dbt Cloud - Environments (dev, staging, prod) - Git version control integration - CI/CD with dbt Cloud
|
| Topic 4: Data Transformation Techniques | 25% | - Jinja templating - Macros and packages - Refactoring and incremental models - Common table expressions and subqueries
|
| Topic 5: dbt Fundamentals | 15% | - dbt project structure - dbt workflow and best practices - dbt Core vs dbt Cloud
|
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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q185-Q190):
NEW QUESTION # 185
You have a time-series fact table, and you're building incremental dbt models for efficiency. Model A loads an initial snapshot; subsequent models process new records only. During a dbt run, a model that processes new data fails. Select the possible consequences:
- A. The initial snapshot will remain intact, but no new data will be updated.
- B. All incremental models will need to be manually rerun after fixing the failed model.
- C. dbt will revert the fact table to a state before the project was ever run.
- D. The initial snapshot and all successfully processed incremental models will be unaffected.
Answer: A,D
Explanation:
A and D are true. Incremental models and snapshot models are designed to work independently within a well-structured dbt project. Failure of one shouldn't affect another. B is incorrect. Dbt doesn't have automatic rollback across entire tables. C is incorrect. Only downstream dependent incremental models would require a rerun, not all of them.
NEW QUESTION # 186
You've included the popular 'dbt-utils' package in your project. Where should you primarily expect to find the models and macros it offers?
- A. Within the 'seeds' directory of your dbt project.
- B. In the 'dbt_project.yml' file under a 'packages' section.
- C. Automatically materialized as new tables in your data warehouse.
- D. Within your 'models' directory namespaced to distinguish them from your own models.
Answer: D
Explanation:
Packages extend your project's functionality by placing items within your model's directory offering seamless integration.
NEW QUESTION # 187
While working on a feature branch, you need to incorporate some critical bug fixes that were merged into the main branch. Which Git commands, or combination of commands, would you use?
- A. Both B and C are viable options.
- B. git rebase main
- C. git checkout main followed by git pull
- D. git merge main
Answer: B,D
Explanation:
B: Rebasing integrates the main branch's changes onto your feature branch, keeping a linear history. C: Merging directly creates a merge commit, making the history slightly less linear but often easier to track when features are integrated.
NEW QUESTION # 188
Select the dbt materialization that typically DOES NOT persist its results to disk:
- A. Incremental
- B. Snapshot
- C. Table
- D. Ephemeral
Answer: D
Explanation:
Ephemeral materializations are computed within CTEs (Common Table Expressions). Their results exist only during the query's execution and are useful for intermediate steps within complex transformations.
NEW QUESTION # 189
You're experimenting with new transformations. You want to iterate on a model without affecting data in the production warehouse. Which dbt command should you use along with appropriate flags?
- A. dbt compile to ensure changes are valid without executing models.
- B. dbt seed with -select to load data into production.
- C. dbt run with -target to specify a development environment.
- D. dbt test with -defer to temporarily bypass upstream dependencies.
Answer: C
Explanation:
The -target flag allows you to isolate development work within different environments preventing accidental changes to production data.
NEW QUESTION # 190
......
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