Why governance ensures data trust in dbt - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to define a source in dbt that includes a description for governance.

dbt

sources:
  - name: my_source
    description: [1]

Drag options to blanks, or click blank then click option'

ANone

B12345

CTrue

D"Source for sales data with governance details"

Attempts:

3 left

💡 Hint

Common Mistakes

Using a number instead of a string for description.

Leaving description empty or None.

The description field should be a clear text explaining the source, which helps in governance by documenting data origins.

2fill in blank

medium

Complete the code to add a freshness check to ensure data trust.

dbt

sources:
  - name: my_source
    freshness:
      [1]: {count: 24, period: hour}

Drag options to blanks, or click blank then click option'

Afail_after

Bwarn_after

Crefresh_interval

Dcheck_frequency

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'fail_after' which causes errors instead of warnings.

Using non-existent keys like 'refresh_interval'.

The warn_after key sets the threshold in hours after which dbt warns if data is stale, supporting data trust.

3fill in blank

hard

Fix the error in the dbt model config to enable governance tags.

dbt

models:
  - name: my_model
    [1]:
      tags: ['governance', 'trusted']

Drag options to blanks, or click blank then click option'

Aconfig

Bconfiguration

Csettings

Doptions

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'configuration' or 'settings' which are invalid keys.

Omitting the config block entirely.

The correct key to configure model properties like tags is config.

4fill in blank

hard

Fill both blanks to create a test that ensures no nulls in a critical column for data trust.

dbt

tests:
  - [1]:
      column_name: [2]

Drag options to blanks, or click blank then click option'

Anot_null

Bunique

Ccustomer_id

Dorder_id

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'unique' test which checks uniqueness, not nulls.

Choosing a non-key column.

The not_null test checks that the specified column has no null values, which is important for data trust.

5fill in blank

hard

Fill all three blanks to define a schema test with severity and tags for governance.

dbt

tests:
  - name: [1]
    severity: [2]
    tags: [[3]]

Drag options to blanks, or click blank then click option'

Aunique_customer_id

Berror

C'governance'

Dwarn

Attempts:

3 left

💡 Hint

Common Mistakes

Using severity 'warn' which only warns but does not fail.

Omitting governance tag.

The test name is 'unique_customer_id', severity is set to 'error' to fail on issues, and the tag 'governance' marks it for governance tracking.

Practice

1. Why is data governance important for building trust in data within a team?

easy

A. It removes the need for data documentation.

B. It makes data processing slower and more complex.

C. It hides data from most team members to avoid confusion.

D. It sets clear rules to keep data accurate and consistent.

Solution

1. Step 1: Understand the role of governance

   Governance creates rules and standards to ensure data is accurate and consistent.

2. Step 2: Connect governance to trust

   When data is accurate and consistent, teams can trust and confidently use it.

3. Final Answer:

   It sets clear rules to keep data accurate and consistent. -> Option D

4. Quick Check:

   Governance = Clear rules = Trust [OK]

Hint: Governance means clear rules for accurate data [OK]

Common Mistakes:

• Thinking governance slows down data use
• Believing governance hides data
• Assuming governance removes documentation

2. Which dbt feature directly supports data governance by checking data quality?

easy

A. dbt models

B. dbt tests

C. dbt snapshots

D. dbt seeds

Solution

1. Step 1: Identify dbt features

   dbt models build data tables, seeds load static data, snapshots track changes, tests check data quality.

2. Step 2: Match feature to governance

   Data governance needs quality checks, which dbt tests provide by validating data correctness.

3. Final Answer:

   dbt tests -> Option B

4. Quick Check:

   Tests = Quality checks = Governance support [OK]

Hint: Tests check data quality to support governance [OK]

Common Mistakes:

• Confusing models with tests
• Thinking snapshots check quality
• Assuming seeds validate data

3. Given this dbt test code snippet, what will be the result if the column user_id contains NULL values?

version: 2
models:
  - name: users
    columns:
      - name: user_id
        tests:
          - not_null

medium

A. The test will fail because NULL values exist in user_id.

B. The test will pass because NULLs are allowed.

C. The test will be ignored by dbt.

D. The test will cause a syntax error.

Solution

1. Step 1: Understand the not_null test

   This test checks that the specified column has no NULL values.

2. Step 2: Analyze the presence of NULLs

   If user_id contains NULLs, the test will detect them and fail.

3. Final Answer:

   The test will fail because NULL values exist in user_id. -> Option A

4. Quick Check:

   not_null test + NULL values = Fail [OK]

Hint: not_null test fails if any NULL found [OK]

Common Mistakes:

• Assuming NULLs pass not_null test
• Thinking test is ignored automatically
• Believing syntax error occurs

4. You wrote this dbt test to ensure no duplicate emails:

tests:
  - unique:
      column_name: email

But it does not run. What is the error?

medium

A. The test name should be unique without parameters.

B. The test should be written as - unique without column_name.

C. The test should be under the columns section with just - unique.

D. The test requires a SQL file, so this YAML is invalid.

Solution

1. Step 1: Check correct test syntax in dbt schema.yml

   Tests on columns go under the columns section with just - unique listed.

2. Step 2: Identify the mistake

   The test is incorrectly placed and uses column_name, which is not valid here.

3. Final Answer:

   The test should be under the columns section with just - unique. -> Option C

4. Quick Check:

   Unique test syntax = under columns with - unique [OK]

Hint: Place tests under columns with simple names [OK]

Common Mistakes:

• Using parameters like column_name in schema tests
• Placing tests outside columns section
• Thinking SQL files are needed for built-in tests

5. Your team wants to ensure data trust by documenting all models and adding tests in dbt. Which combination best supports governance?

hard

A. Write detailed model descriptions and add tests like not_null and unique on key columns.

B. Only add tests without documentation to save time.

C. Document models but skip tests since they slow down builds.

D. Use snapshots only to track data changes without tests or docs.

Solution

1. Step 1: Understand governance needs

   Governance requires both clear documentation and data quality checks to build trust.

2. Step 2: Evaluate options

   Write detailed model descriptions and add tests like not_null and unique on key columns. combines documentation and tests, supporting governance best. Others skip key parts.

3. Final Answer:

   Write detailed model descriptions and add tests like not_null and unique on key columns. -> Option A

4. Quick Check:

   Docs + tests = Strong governance [OK]

Hint: Combine docs and tests for best governance [OK]

Common Mistakes:

• Skipping docs or tests thinking one is enough
• Avoiding tests to speed builds
• Relying only on snapshots for trust