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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

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

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q105-Q110):

NEW QUESTION # 105
dbt Model Snippet

A. The ref() functions arent correctly resolving dependencies.
B. The underlying data types of o.customer_id and c.customer_id mismatch.
C. The logic contained within a custom macro.
D. The presence of filters on the source fct_orders or dim_customers.

Answer: D

Explanation:
Filters on sources frequently cause missing rows in joins. Check your source definitions and any model- level filtering. While the others could be issues, start with the most common cause.

NEW QUESTION # 106
You introduce a custom macro into your project. This is a snippet of your dbt_project.yml:YAML

A. The .sql extension on the file within the macros directory is incorrect.
B. You must place the macros directory within the root of your dbt project.
C. The macro_paths configuration in your dbt_project.yml might be incorrect or missing.
D. The macro's name should only be 'trim', without the 'string_utils' prefix.

Answer: C

Explanation:
Check your macro file paths, as an incorrect configuration would prevent dbt from finding the macro. The others are likely not the issue but worth double-checking.

NEW QUESTION # 107
dbt Model Snippet:SQL

A. The GROUP BY month clause leading to duplicate rows.
B. The SUM(order_amount) aggregation logic.
C. The source() function retrieving data from the incorrect schema.
D. Incorrect Jinja usage within a macro used for templating.

Answer: B

Explanation:
Focus on the calculation itself, as the rest of the structure seems expected. The source reference and grouping appear standard.

NEW QUESTION # 108
You are building an incremental model.
Identify the circumstances in which is_incremental() would evaluate to True or False.

Answer:

Explanation:

Explanation:
1. There is a config block at the top of the model with materialized = 'table'
## Answer: False
2. The corresponding table already exists in the data warehouse
## Answer: True
3. The incremental model was executed with the --full-refresh flag
## Answer: False
4. The corresponding table does not already exist in the data warehouse
## Answer: False
The is_incremental() macro in dbt is used within an incremental model to determine whether the current invocation should perform an incremental update or a full rebuild. It evaluates to True only during an incremental run when the target table already exists in the data warehouse and dbt is not performing a full refresh.
For is_incremental() to return True, two conditions must be met:
* The model must be materialized as incremental, not table or view.Therefore, if the config specifies materialized = 'table', the model is not incremental, and the function evaluates to False.
* The table already exists in the target schema.In this case, dbt will run the model in incremental mode, making is_incremental() return **True`.
If the incremental model is run with --full-refresh, dbt intentionally rebuilds the entire table, meaning is_incremental() evaluates to False, even if the table exists.
Lastly, if the target table does not exist yet, dbt must create it from scratch, so the run is treated as a full rebuild, not an incremental update, causing is_incremental() to evaluate to False.
Thus, the only scenario where is_incremental() returns True is when the table exists and the model is actually incremental.

NEW QUESTION # 109
(Multiple Select)

A. You want to test different loading strategies for a large source table.
B. You need to apply custom column-level transformations to a raw source.
C. The source data is sensitive and requires role-based access control.
D. The source has multiple tables with related schemas requiring standardization.

Answer: B,D

Explanation:
yml files allow for complex source schemas and column transformations. Access control and loading strategies are usually handled at the database or project-level configuration.

NEW QUESTION # 110
......

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