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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Managing Data Pipelines | 15% | - Pipeline orchestration - CI/CD integration - Deployment strategies |
| Topic 2: Implementing dbt Tests | 10% | - Built-in tests - Custom tests - Test configuration and execution |
| Topic 3: Debugging and Error Resolution | 15% | - Resolving data quality issues - Debugging techniques - Identifying modeling errors |
| Topic 4: Developing dbt Models | 20% | - Model optimization
|
| Topic 5: External Dependencies | 10% | - External sources integration - Managing snapshots - Using packages |
| Topic 6: dbt Models Governance | 15% | - Project organization and structure - Naming conventions and standards - Version control integration |
| Topic 7: Creating and Maintaining Documentation | 10% | - Descriptions and metadata - Generating documentation - Documentation standards |
| Topic 8: Leveraging dbt State | 5% | - State-aware operations - State management |
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NEW QUESTION # 122
A colleague has introduced a new sensitive column into a source table. You need to update the dbt project documentation accordingly. Which of the following actions should you take?
Answer: A,B,C
Explanation:
B). Tagging sensitive data helps categorize it, allowing for potential filtering or access control within the documentation. C: Handling sensitive data goes beyond simple documentation. Its crucial to follow your organization's data security and governance protocols. D: Referencing source documentation provides full context and traceability of the sensitive data's origin.
NEW QUESTION # 123
You are working with git to version control the dbt logic.
Order these steps to add or modify transformations to your dbt project.
Answer:
Explanation:
* Create a new branch in git and switch to itB. Update the dbt code according to the new logic
C. Create a Pull / Merge RequestD. Run some automated CI checks and/or manual review of the updated codeE. Merge the updated code to the main git branch
* Version control best practices in dbt follow the same engineering workflow used in modern software development. The first step is always to create a new git branch and switch into it, ensuring all work is isolated from production-ready code and allowing your team to develop safely without affecting others.
Once inside the feature branch, you update the dbt code according to the new logic, which may include modifying models, tests, macros, or documentation.
* Next, you create a Pull Request (PR), also known as a Merge Request, to propose integrating your changes into the main branch. This is important because dbt projects are collaborative, and PRs facilitate peer review, enforce project standards, and prevent regressions. Once the PR is created, automated CI pipelines-such as running dbt build, schema tests, data quality checks, and code-style checks-are executed. Reviewers may also manually inspect code for logic correctness, naming conventions, and modeling consistency.
* After all checks have passed and reviewers approve the PR, the final step is to merge the updated code into the main branch, making the new transformations part of the production dbt project. This workflow ensures governance, reliability, and auditable development practices, all of which are core principles in analytics engineering.
NEW QUESTION # 124
Your company wants to standardize pull request templates. Which information would be beneficial to include in such a template?
Answer: D
Explanation:
A: Checklists ensure core quality steps are followed. B: Linking design documents provides context for reviewers. C: Guidance helps reviewers focus their feedback.
NEW QUESTION # 125
You run the command:
dbt test --select 'test_type:singular'
What will the command run?
Options shown:
Answer: A
Explanation:
In dbt, singular tests are custom SQL tests that live as standalone .sql files inside the root /tests directory, not inside /tests/generic. A singular test returns rows that indicate failure, and dbt runs the SQL directly as written. Generic tests, on the other hand, live inside the /tests/generic folder and are YAML-based macro- driven tests.
From your test folder structure (shown in the original screenshot), the following SQL files exist:
Inside /tests/generic/
* furniture_customers_test.sqlThis file is a generic test, not singular.
Inside the root /tests directory:
* macro_stg_tpch_orders_assert_pos_price.sql
* macro_stg_tpch_suppliers_assert_pos_acct_bal.sql
* stg_tpch_orders_assert_positive_price.sql
These are singular tests, because they are standalone SQL files in the tests root folder.
When you run:
dbt test --select 'test_type:singular'
dbt filters for only tests classified as singular. It ignores generic tests entirely.
Therefore, only the following 3 tests will run:
* macro_stg_tpch_orders_assert_pos_price
* macro_stg_tpch_suppliers_assert_pos_acct_bal
* stg_tpch_orders_assert_positive_price
This matches Option C, making it the correct answer.
NEW QUESTION # 126
(Multiple Select)
Answer: A,B
Explanation:
seeds are ideal for static reference data and environment-specific configurations. Large data backfills are usually handled outside of 'seeds'. Generic tests would be defined in the tests section.
NEW QUESTION # 127
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