Materializations strategy in dbt - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding dbt Materializations

Which of the following best describes the incremental materialization strategy in dbt?

A It creates a temporary table that is dropped after the run completes.

B It creates a view that dynamically queries the source data without storing results.

C It appends only new or changed data to the existing table, avoiding full rebuilds.

D It rebuilds the entire table from scratch every time the model runs.

💡 Hint

Think about how to save time by not rebuilding everything every time.

The incremental materialization updates only new or changed data, making runs faster by avoiding full rebuilds.

❓ Predict Output

intermediate

Output of a dbt model with 'view' materialization

Given this dbt model materialized as a view, what will be the result when querying the model?

select id, count(*) as cnt from source_table group by id

A A view that runs the aggregation query on source_table each time it is queried.

B A physical table storing aggregated counts for each id.

C An error because views cannot have aggregation.

D A temporary table that disappears after the dbt run.

💡 Hint

Remember what a view does in SQL databases.

A view stores the query logic but does not store data physically. It runs the query fresh each time.

❓ data_output

advanced

Resulting table rows after incremental materialization

Assume a dbt incremental model starts with this table:

id | value
1  | 10
2  | 20
3  | 30

New data to add is:

id | value
2  | 25
4  | 40

After running the incremental model that updates existing ids and inserts new ones, what will the final table contain?

A

id | value
1  | 10
3  | 30
4  | 40

B

id | value
1  | 10
2  | 20
3  | 30
4  | 40

C

id | value
2  | 25
4  | 40

D

id | value
1  | 10
2  | 25
3  | 30
4  | 40

💡 Hint

Think about how incremental updates replace existing rows and add new ones.

The incremental model updates id 2's value to 25 and inserts id 4 with value 40, keeping other rows unchanged.

🔧 Debug

advanced

Debugging a failing incremental model

A dbt incremental model fails with this error: "relation 'my_table' does not exist" when running for the first time. What is the most likely cause?

A The source table is missing required columns for incremental logic.

B The model is set to incremental but the table does not exist yet, and the code does not handle the initial full build.

C The model is set to view materialization but uses incremental syntax.

D The database user lacks permission to create views.

💡 Hint

Think about what happens the first time an incremental model runs.

Incremental models must handle the case when the target table does not exist yet, usually by running a full build on first run.

🚀 Application

expert

Choosing the best materialization for a large slowly changing dataset

You have a large dataset that updates slowly with occasional new rows and updates. You want to minimize compute costs and keep data fresh. Which dbt materialization strategy is best?

A Incremental materialization, updating only changed or new rows.

B View materialization, querying source data live every time.

C Table materialization, rebuilding the entire table every run.

D Ephemeral materialization, embedding logic in downstream models.

💡 Hint

Consider cost and freshness trade-offs for large datasets.

Incremental materialization updates only changed data, saving compute and keeping data fresh without full rebuilds.