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dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. You're tasked with creating a model for audit purposes. The data must be preserved exactly as it was at a specific point in time. Update frequency is low, and there's no need for additional transformations on the captured dat a. What materialization should you use?

A) Snapshot
B) Table
C) Incremental
D) View

2. You need to build a model to identify customers who haven't placed orders in the past 90 days. Performance with this model is critical, as it will trigger a re-engagement campaign. Which strategy is likely to yield the best results?

A) Join the customers and orders table, group by customer ID and use a HAVING clause to filter inactive customers.
B) IJse a window function to rank order dates for each customer and filter those where the most recent order is older than 90 days.
C) Filter the orders table for dates within the past 90 days, then find customers without corresponding order IDs.
D) Create a materialized view that contains only active customers and join against the orders table.

3. You're refactoring a complex dbt model and realize breaking it down into smaller models would improve readability. However, you're concerned about performance overhead due to the additional materializations. How would you address this concern?

A) Rely on source freshness checks to determine if intermediate models need to be rebuilt_
B) Switch to incremental materializations for all intermediate models.
C) Profile your models to pinpoint bottlenecks and optimize those specifically.
D) Utilize ephemeral materializations for intermediate steps, where appropriate_

4. You want to compare the current version of a file in your working directory to the most recently committed version. Which Git command would be most helpful?

A) git status
B) git diff
C) git log
D) git show

5. You encounter a runtime error: "Column 'order_date' not found in the target relation". You examine your model and see:SQL

A) Review the fct_orders model's SQL logic to see if it unintentionally removes or renames the 'order_date' column.
B) Verify that your Jinja templating in other models isn't interfering with column names.
C) Check if the fct_orders model or source actually includes an 'order_date' column.
D) Ensure there are no downstream models that could be altering the 'fct_orders' table.

Solutions: