dbt Analytics Engineering Practice Questions

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Topic 1: Developing dbt models

A BigQuery project has a staging model stg_accounts and a mart model fct_accounts. The mart currently queries analytics_dev.stg_accounts directly. What is the best change before promoting to production?

A Replace the hard-coded relation with ref('stg_accounts') check_circle

B Replace the model with a seed named stg_accounts

C Move the SQL into profiles.yml

D Add a source freshness check to the mart only

lightbulb

Explanation

ref() resolves the correct relation per target and records DAG dependencies. Hard-coding a development schema is brittle and source freshness does not connect dbt models.

Topic 1: Developing dbt models

A BigQuery project has a staging model stg_assets and a mart model fct_assets. The mart currently queries analytics_dev.stg_assets directly. What is the best change before promoting to production?

A Replace the hard-coded relation with ref('stg_assets') check_circle

B Replace the model with a seed named stg_assets

C Move the SQL into profiles.yml

D Add a source freshness check to the mart only

lightbulb

Explanation

ref() resolves the correct relation per target and records DAG dependencies. Hard-coding a development schema is brittle and source freshness does not connect dbt models.

Topic 1: Developing dbt models

A BigQuery project has a staging model stg_campaigns and a mart model fct_campaigns. The mart currently queries analytics_dev.stg_campaigns directly. What is the best change before promoting to production?

A Replace the hard-coded relation with ref('stg_campaigns') check_circle

B Replace the model with a seed named stg_campaigns

C Move the SQL into profiles.yml

D Add a source freshness check to the mart only

lightbulb

Explanation

ref() resolves the correct relation per target and records DAG dependencies. Hard-coding a development schema is brittle and source freshness does not connect dbt models.

Topic 1: Developing dbt models

A BigQuery project has a staging model stg_contracts and a mart model fct_contracts. The mart currently queries analytics_dev.stg_contracts directly. What is the best change before promoting to production?

A Replace the hard-coded relation with ref('stg_contracts') check_circle

B Replace the model with a seed named stg_contracts

C Move the SQL into profiles.yml

D Add a source freshness check to the mart only

lightbulb

Explanation

ref() resolves the correct relation per target and records DAG dependencies. Hard-coding a development schema is brittle and source freshness does not connect dbt models.

Topic 1: Developing dbt models

A BigQuery project has a staging model stg_impressions and a mart model fct_impressions. The mart currently queries analytics_dev.stg_impressions directly. What is the best change before promoting to production?

A Replace the hard-coded relation with ref('stg_impressions') check_circle

B Replace the model with a seed named stg_impressions

C Move the SQL into profiles.yml

D Add a source freshness check to the mart only

lightbulb

Explanation

ref() resolves the correct relation per target and records DAG dependencies. Hard-coding a development schema is brittle and source freshness does not connect dbt models.

Topic 1: Developing dbt models

A BigQuery project has a staging model stg_inventory and a mart model fct_inventory. The mart currently queries analytics_dev.stg_inventory directly. What is the best change before promoting to production?

A Replace the hard-coded relation with ref('stg_inventory') check_circle

B Replace the model with a seed named stg_inventory

C Move the SQL into profiles.yml

D Add a source freshness check to the mart only

lightbulb

Explanation

ref() resolves the correct relation per target and records DAG dependencies. Hard-coding a development schema is brittle and source freshness does not connect dbt models.

Topic 1: Developing dbt models

A BigQuery project has a staging model stg_invoices and a mart model fct_invoices. The mart currently queries analytics_dev.stg_invoices directly. What is the best change before promoting to production?

A Replace the hard-coded relation with ref('stg_invoices') check_circle

B Replace the model with a seed named stg_invoices

C Move the SQL into profiles.yml

D Add a source freshness check to the mart only

lightbulb

Explanation

ref() resolves the correct relation per target and records DAG dependencies. Hard-coding a development schema is brittle and source freshness does not connect dbt models.

Topic 1: Developing dbt models

A BigQuery project has a staging model stg_line_items and a mart model fct_line_items. The mart currently queries analytics_dev.stg_line_items directly. What is the best change before promoting to production?

A Replace the hard-coded relation with ref('stg_line_items') check_circle

B Replace the model with a seed named stg_line_items

C Move the SQL into profiles.yml

D Add a source freshness check to the mart only

lightbulb

Explanation

ref() resolves the correct relation per target and records DAG dependencies. Hard-coding a development schema is brittle and source freshness does not connect dbt models.

Topic 1: Developing dbt models

A BigQuery project has a staging model stg_page_views and a mart model fct_page_views. The mart currently queries analytics_dev.stg_page_views directly. What is the best change before promoting to production?

A Replace the hard-coded relation with ref('stg_page_views') check_circle

B Replace the model with a seed named stg_page_views

C Move the SQL into profiles.yml

D Add a source freshness check to the mart only

lightbulb

Explanation

ref() resolves the correct relation per target and records DAG dependencies. Hard-coding a development schema is brittle and source freshness does not connect dbt models.

Topic 1: Developing dbt models

A BigQuery project has a staging model stg_payments and a mart model fct_payments. The mart currently queries analytics_dev.stg_payments directly. What is the best change before promoting to production?

A Replace the hard-coded relation with ref('stg_payments') check_circle

B Replace the model with a seed named stg_payments

C Move the SQL into profiles.yml

D Add a source freshness check to the mart only

lightbulb

Explanation

ref() resolves the correct relation per target and records DAG dependencies. Hard-coding a development schema is brittle and source freshness does not connect dbt models.

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