Store test failures for analysis in dbt - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the purpose of storing test failures in dbt?

Storing test failures helps you analyze and understand why data quality checks failed. It allows you to track issues over time and fix data problems effectively.

intermediate

How can you capture test failure details in dbt?

You can capture test failure details by configuring dbt to write test results to a table or by using custom SQL tests that insert failure records into a dedicated table for analysis.

intermediate

What is a common method to store test failures for later analysis in dbt?

A common method is to create a table that stores rows which fail tests, using SQL tests that insert failing rows into this table during dbt runs.

beginner

Why is it helpful to analyze stored test failures over time?

Analyzing stored failures helps identify recurring data issues, track improvements, and prioritize fixes, improving overall data reliability.

advanced

What dbt feature can you use to automate storing test failures?

You can use dbt's custom tests combined with post-hook SQL statements to automatically insert failure details into a table after tests run.

What does storing test failures in dbt help you do?

A Delete old data

B Speed up data loading

C Create new data models

D Analyze and fix data quality issues

Storing test failures helps analyze and fix data quality issues by keeping track of what failed.

Which method can be used to store test failures in dbt?

A Export data to Excel manually

B Create a table and insert failing rows using SQL tests

C Only use built-in dbt logs

D Run dbt without tests

Creating a table and inserting failing rows via SQL tests is a common way to store failures for analysis.

What is a benefit of analyzing stored test failures over time?

A Make data models slower

B Increase data storage costs

C Identify recurring data problems

D Hide errors from users

Analyzing failures helps identify recurring problems so you can fix them.

Which dbt feature helps automate storing test failures?

A Custom tests with post-hook SQL

B dbt seed files

C dbt snapshot

D dbt docs generation

Custom tests combined with post-hook SQL can automate inserting failure details into tables.

What type of data is stored when capturing test failures?

A Rows that did not pass the test

B All rows in the dataset

C Only metadata about the test

D User login information

You store the rows that failed the test to understand what data caused the failure.

Explain how you can store test failures in dbt for later analysis.

Think about using custom SQL tests and tables.

Why is it important to analyze stored test failures over time?

Consider the benefits of tracking problems.