Why governance ensures data trust in dbt

Introduction

Governance helps make sure data is correct and safe. This builds trust so people can use data with confidence.

When sharing data across teams in a company

When making important decisions based on data

When tracking data changes over time

When ensuring data follows rules and laws

When preventing mistakes or misuse of data

Syntax

dbt

-- Example of a dbt model with governance comments
-- This model selects clean customer data
select
  id,
  name,
  email
from raw.customers
where email is not null

dbt models are SQL files that transform raw data.

Adding comments helps explain data rules and checks.

Examples

This model filters out customers without emails to keep data clean.

dbt

-- Model with data quality test
select
  id,
  name,
  email
from raw.customers
where email is not null

Descriptions help users understand what the data means.

dbt

-- Adding a description in dbt schema.yml
models:
  - name: customers
    description: "Cleaned customer data with valid emails"

Sample Program

This example shows a dbt model that filters out customers without emails. The schema.yml file adds descriptions and tests to ensure data quality. These governance steps help users trust the data.

dbt

-- dbt model: models/customers.sql
select
  id,
  name,
  email
from raw.customers
where email is not null

-- dbt schema.yml snippet
models:
  - name: customers
    description: "Cleaned customer data with valid emails"
    tests:
      - not_null:
          column_name: email
      - unique:
          column_name: id

Important Notes

Governance includes documentation, testing, and access control.

dbt makes it easy to add tests that catch data problems early.

Clear descriptions help everyone understand data purpose and limits.

Summary

Governance builds trust by making data reliable and understandable.

dbt supports governance with tests and documentation.

Good governance helps teams use data safely and confidently.

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