Free Data Build Tool dbt-Analytics-Engineering Exam Questions

Question 1

You work at an e-commerce company and a vendor provides their inventory data via CSV file uploads to an S3 bucket. How do you prep the data for dbt transformations? Choose 1 option.

A : Create a dbt model with a view querying the external table directly.

B : Run a pre-hook to create a temporary table and query from it in a staging model.

C : Use dbt seed to stage the data in your data platform.

D : Declare the external table as a source using the external configuration.

Answer: D

Question 2

Examine how freshness is defined at the database level:- name: rawdatabase: rawfreshness: # default freshnesswarn_after: {count: 12, period: hour}error_after: {count: 24, period: hour}loaded_at_field: _etl_loaded_atHow can one table from the source raw be excluded from source freshness?

A : Add freshness: null to the table configuration.

B : Since freshness is defined at the source level, all tables in the source must adhere to the freshness parameters.

C : Add loaded_at_field: null to the table configuration.

D : Add error_after: null to the table configuration.

Answer: A

Question 3

Which of the following is true about restricting the usage of models in dbt? Choose 1 option.

A : Restrictions are set by defining the models and Git user groups approved for usage.

B : You must map your data platform roles to groups by specifying the role name in the configurations.

C : Model groups can limit references by other models which aren’t in the same group.

D : Data platform user emails can be used to determine who can reference a model.

Answer: C

Question 4

Examine how freshness is defined at the database level:- name: rawdatabase: rawfreshness: # default freshnesswarn_after: {count: 12, period: hour}error_after: {count: 24, period: hour}loaded_at_field: _etl_loaded_atHow can one table from the source raw be excluded from source freshness?

A : Add freshness: null to the table configuration.

B : Since freshness is defined at the source level, all tables in the source must adhere to the freshness parameters.

C : Add loaded_at_field: null to the table configuration.

D : Add error_after: null to the table configuration.

Answer: A

Question 5

Consider these SQL and YAML files for the model model_a: models/staging/model_a.sql {{ config( materialized = "view" ) }} with customers as ( ... ) dbt_project.yml models: my_new_project: +materialized: table staging: +materialized: ephemeral Which is true about model_a? Choose 1 option.

A : Select statements made from the database on top of model_a and transformation processing within model_a will be quicker, but the data will only be as up to date as the last dbt run.

B : Select statements made from the database on top of model_a will result in an error.

C : Select statements made from the database on top of model_a will be slower, but the data will always be up to date.

D : Select statements made from the database on top of model_a will be quicker, but the data will only be as up to date as the last dbt run.

Answer: C