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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

Section	Weight	Objectives
dbt Models Governance	15%	- Naming conventions and standards - Project organization and structure - Version control integration
Debugging and Error Resolution	15%	- Resolving data quality issues - Identifying modeling errors - Debugging techniques
Creating and Maintaining Documentation	10%	- Descriptions and metadata - Generating documentation - Documentation standards
External Dependencies	10%	- Managing snapshots - External sources integration - Using packages
Managing Data Pipelines	15%	- CI/CD integration - Pipeline orchestration - Deployment strategies
Developing dbt Models	20%	- Model optimization 1. Model contracts 2. Performance tuning - Model design and structure 1. Materialization types 2. Ref and source functions 3. Incremental models
Leveraging dbt State	5%	- State-aware operations - State management
Implementing dbt Tests	10%	- Custom tests - Test configuration and execution - Built-in tests

>> dbt-Analytics-Engineering合格内容 <<

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dbt Labs dbt Analytics Engineering Certification Exam 認定 dbt-Analytics-Engineering 試験問題 (Q334-Q339):

質問 # 334
You're onboarding a new team member and need to set them up with a personal sandbox environment within your existing project. What factors do you need to consider?

A. Whether they need access to production data replicas and how to control this securely
B. How to configure a profile on their machine and guide them to isolate changes to their sandbox.
C. How to provision data warehouse resources if needed, such as a separate schema or potentially even a dedicated database.
D. All of the above.

正解：D

解説：
A: Resource allocation impacts security and costs. B. Sandbox access should align with the developer's role and data privacy requirements. C: Setting up the developer's machine and workflow is essential-

質問 # 335
You want to include a multi-paragraph description for a source. Which of the following approaches is the most suitable?

A. Reference an external Markdown file within the source description.
B. Write a longer description directly within the YAML file, breaking it across multiple lines.
C. Utilize YAML's block scalar syntax (using l) to maintain formatting for multi-line descriptions.
D. dbt documentation does not support multi-paragraph descriptions for sources.

正解：C

解説：
The block scalar syntax in YAML allows for writing multi-line text blocks that preserve the original formatting

質問 # 336
(Multiple Select)

A. Ensure relevant columns in underlying tables have appropriate indexes.
B. Utilize window functions to efficiently compute the difference without self-joins.
C. Pre-calculate frequently used periods (e.g., current month, previous month) and store them as intermediate CTEs.
D. Introduce redundant columns in source tables to store pre-calculated percentage changes.

正解：A、B

解説：
Window functions excel at period-over-period calculations. Indexes are crucial for accelerating queries. Options A and B could help but introduce potential maintenance and storage tradeoffs.

質問 # 337
You need to grant readonly access to the results of your dbt project to stakeholders outside your team. Considering security, which approach would be the MOST suitable?

A. Have stakeholders directly query the dbt models, providing access to the production data warehouse.
B. Regularly run dbt seed to export CSV files, which are then shared with stakeholders.
C. Create a designated reporting schema and set up views that map to the dbt model outputs
D. Embed dbt model results within a Bl dashboard and manage access through the Bl tool.

正解：C、D

解説：
A provides fine-grained control within the database. C uses the Bl tool for the access management layer. B is too broad in terms of access. D is manual and less secure.

質問 # 338
Several models perform similar filtering and aggregation on a frequently used source table. What's the most effective way to streamline this process and improve maintainability?

A. Create a snapshot to capture the pre-processed state of the source table.
B. Create an ephemeral model to prepare the data in a common format, referenced by downstream models.
C. Create a table materialization to hold the pre-processed data.
D. Replicate the filtering and aggregation logic directly within each model.

正解：B

解説：
Ephemeral models within CTEs allow for reusable intermediate steps in data transformation and are perfect for avoiding logic duplication across multiple models.

質問 # 339
......

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