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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: dbt Fundamentals | 15% | - dbt workflow and best practices - dbt project structure - dbt Core vs dbt Cloud |
| Topic 2: Models | 25% | - Sources and references - Materializations (table, view, ephemeral, incremental) - Seeds - Snapshots - Writing and managing SQL models |
| Topic 3: Testing and Documentation | 20% | - Custom data tests - Schema tests (unique, not_null, accepted_values, relationships) - Documentation generation - dbt docs and DAG visualization |
| Topic 4: Data Transformation Techniques | 25% | - Refactoring and incremental models - Jinja templating - Macros and packages - Common table expressions and subqueries |
| Topic 5: Deployment and Orchestration | 15% | - Git version control integration - CI/CD with dbt Cloud - Environments (dev, staging, prod) - Jobs and scheduling in dbt Cloud |
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NEW QUESTION # 295
You're refactoring a complex SQL query into a dbt model. You notice that the model's output has significantly fewer rows than expected. Which of the following are potential causes?
Answer: B,C,D
Explanation:
All except D could limit the result set more than expected. Materialization settings impact how tables are built, not the SQL logic itself.
NEW QUESTION # 296
(Multiple Select)
Answer: B,C
Explanation:
Contributing to open-source is great, but you likely need an immediate fix. Overriding gives you control while addressing the issue upstream. Forking is feasible, but the maintenance burden might outweigh the benefits.
NEW QUESTION # 297 
Answer:
Explanation:
Explanation:
Drops and recreates a definition of a query which is executed at the time it's referenced
# view
Inserts or updates records of an existing object in the warehouse using a delta
# incremental
Code belonging to the model is inserted into the places the model is referenced
# ephemeral
Drops and recreates an object in the warehouse as stored results when using dbt run
# table
NEW QUESTION # 298
Given this dbt_project.yml:
name: "jaffle_shop"
version: "1.0.0"
config-version: 2
profile: "snowflake"
model-paths: ["models"]
macro-paths: ["macros"]
snapshot-paths: ["snapshots"]
target-path: "target"
clean-targets:
- "logs"
- "target"
- "dbt_modules"
- "dbt_packages"
models:
jaffle_shop:
orders:
materialized: table
When executing a dbt run your models build as views instead of tables:
19:36:14 Found 1 model, 0 tests, 0 snapshots, 0 analyses, 179 macros, 0 operations, 0 seed files, 0 sources, 0 exposures, 0 metrics
19:36:16 Concurrency: 1 threads (target='default')
19:36:17 Finished running 1 view model in 3.35s.
19:36:17 Completed successfully
19:36:17 Done. PASS=1 WARN=0 ERROR=0 SKIP=0 TOTAL=1
Which could be a root cause of why the model was not materialized as a table?
The target-path is incorrectly configured.
Answer: A
Explanation:
The behavior described-dbt running the orders model as a view despite being explicitly configured as a table
-indicates that dbt is not correctly detecting or applying the model-level configuration during compilation.
dbt relies heavily on the target-path directory to write compiled SQL, manifest files, and run artifacts. If the target-path is misconfigured, pointing to a location that dbt does not handle correctly or that overlaps with another folder used internally, dbt may fail to load the correct configuration from the merged project settings.
When dbt cannot locate the compiled configuration for a model, it defaults to its standard materialization type, which is view. This explains why the logs show:
"Finished running 1 view model"
even though the dbt_project.yml clearly declares:
materialized: table.
Additionally, the logs indicate no warnings or parsing errors, meaning dbt ran successfully but with incorrect settings-another indicator of configuration metadata being overridden or misplaced due to an incorrect target- path.
By resolving the target-path issue, dbt will successfully load the model configuration and materialize the orders model as a table as intended.
NEW QUESTION # 299
You must exclude a specific model from being included in the generated documentation entirely. How would you achieve this?
Answer: D
Explanation:
The enabled flag in dbt_project.yml provides control over whether a model (or other resources) are includedin dbt operations, including doc generation. Check your dbt version documentation for the latest syntax
NEW QUESTION # 300
......
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