Free PDF Quiz dbt-Analytics-Engineering - dbt Analytics Engineering Certification Exam Authoritative Test Answers

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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

Section	Objectives
Topic 1: Testing and Data Quality	- Built-in and custom tests 1. Custom SQL tests 2. Generic tests (unique, not null, relationships) - Data validation strategies 1. CI-based validation workflows 2. Schema testing practices
Topic 2: Analytics Engineering Foundations	- Modern data stack concepts (ELT vs ETL) 1. Warehouse-centric transformation workflows 2. Role of dbt in analytics engineering - SQL proficiency for analytics 1. Data modeling in SQL 2. Joins, aggregations, and window functions
Topic 3: Documentation and Lineage	- Data lineage understanding 1. Dependency tracking with ref() 2. Directed acyclic graph (DAG) - dbt documentation system 1. Model descriptions and metadata 2. Auto-generated docs site
Topic 4: Deployment and Orchestration	- Environments and workflows 1. Version control with Git 2. Development vs production environments - Running dbt in production 1. CI/CD integration patterns 2. dbt Cloud and job scheduling
Topic 5: dbt Core Concepts	- Models and materializations 1. Ref and source functions 2. Views, tables, incremental models - Project structure and configuration 1. dbt_project.yml configuration 2. Packages and dependencies

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q109-Q114):

NEW QUESTION # 109
You're collaborating on a branch and need to temporarily switch to a different branch to address an urgent hotfix. Which Git command allows you to save your current uncommitted work without interrupting the changes on your active branch?

A. git push
B. git stash
C. git reset
D. git stage

Answer: B

Explanation:
git stash temporarily stores your uncommitted changes, enabling you to switch branches and later reapply those changes using git stash pop.

NEW QUESTION # 110
You want to include a glossary of terms in your dbt project docs so that users can easily reference definitions. How could you achieve this?

A. Create a separate YAML file for your glossary, and use a Jinja macro to incorporate it into the documentation template.
B. Manually add a separate "Glossary" page to the generated docs after running dbt docs generate_
C. Use the meta configuration in your dbt_project_yml file to define the glossary terms and their meanings.
D. Utilize a custom macro in your models to automatically generate a glossary section from designated column descriptions.

Answer: A,D

Explanation:
A: A flexible approach with Jinja macros and a glossary file allows you to dynamically include your glossary in the documentation_ D. Custom macros can provide automation by extracting glossary terms from specifically marked column descriptions.

NEW QUESTION # 111
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. Utilize a dbt package to export specific models to CSV or JSON format and provide those files to the vendor
B. Set up a data sharing mechanism through your data warehouse, if it supports this functionality, enabling controlled access.
C. A combination of the above might be needed, depending on the vendor's integration capabilities-
D. Generate a dedicated readout schema in your data warehouse with appropriate grants for the vendor's user

Answer: C

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 # 112
A complex transformation in your dbt project pulls data from an external API. Due to rate limits, this API endpoint cannot be queried frequently in production. How could you handle development and testing of this transformation effectively?

A. All of the above could be part of a strategy.
B. Utilize dbt snapshots to capture a static set of API data for use during development and testing.
C. Use environment variables to control API query frequency or switch between live and test data sources.
D. Set up a development environment that utilizes a mock API to simulate external data.

Answer: A

Explanation:
A: Mocks enable testing without impacting the production API- B: Environment variables allow for flexible configuration. C: Snapshots provide static samples for testing in isolation.

NEW QUESTION # 113
A colleague has made updates to some model descriptions and wants you to quickly regenerate the docs to only include those changes. Which command variation would be the most efficient without a full recompilation?

A. dbt docs generate --models +[model_namel
B. Utilize dbt's incremental model feature along with dbt docs generate -no-compile.
C. dbt docs generate -select [model_name]
D. It's not possible to partially regenerate dbt docs; you need to run the full dbt docs generate command.

Answer: C

Explanation:
The -select flag limits the documentation generation to the specified model(s). However, for this to work smoothly, dependencies need to be considered. If the updated model depends on others, they might need to be included or recompiled for the docs to be correct.

NEW QUESTION # 114
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