Data lineage tracking in Snowflake - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is data lineage tracking in Snowflake?

Data lineage tracking is the process of recording the origin, movement, and transformation of data within Snowflake. It helps understand where data comes from, how it changes, and where it goes.

intermediate

Which Snowflake feature helps track data lineage automatically?

Snowflake's Information Schema and Account Usage views provide metadata about queries, tables, and objects, which can be used to track data lineage.

beginner

Why is data lineage important in cloud data platforms like Snowflake?

Data lineage ensures data quality, helps with troubleshooting, supports compliance, and improves trust by showing how data flows and changes over time.

intermediate

How can you use Snowflake's QUERY_HISTORY view for data lineage?

QUERY_HISTORY shows past queries with details on input and output tables. By analyzing it, you can see which tables were read or written, helping trace data flow.

advanced

What is a best practice for maintaining accurate data lineage in Snowflake?

Use consistent naming conventions, document transformations, and regularly audit metadata views like QUERY_HISTORY and INFORMATION_SCHEMA to keep lineage clear and reliable.

What does data lineage tracking help you understand in Snowflake?

A Where data comes from and how it changes

B How to write SQL queries faster

C How to create user accounts

D How to backup data manually

Data lineage tracking shows the origin and transformation of data, not query speed or user management.

Which Snowflake view contains information about past queries useful for data lineage?

A SESSION_LOGS

B USER_ACCOUNTS

C STORAGE_USAGE

D QUERY_HISTORY

QUERY_HISTORY contains details about executed queries, including input and output tables.

Why is data lineage important for compliance?

A It deletes old data

B It shows how data is handled and transformed

C It encrypts data automatically

D It speeds up data loading

Data lineage helps prove data handling processes meet compliance requirements.

Which Snowflake metadata schema helps with data lineage?

A DATA_SCHEMA

B USER_SCHEMA

C INFORMATION_SCHEMA

D LOG_SCHEMA

INFORMATION_SCHEMA provides metadata about tables, views, and other objects.

What is a good practice to keep data lineage clear?

A Use consistent naming and document transformations

B Avoid using metadata views

C Delete query history frequently

D Store data only in external files

Consistent naming and documentation help maintain clear and reliable data lineage.

Explain how Snowflake's QUERY_HISTORY view can be used to track data lineage.

Think about how queries read and write tables.

Describe why data lineage tracking is important in cloud data platforms like Snowflake.

Consider the benefits of knowing data origins and changes.

Practice

1. What is the main purpose of data lineage tracking in Snowflake?

easy

A. To increase storage capacity automatically

B. To show where data comes from and how it moves

C. To encrypt data at rest

D. To create user accounts

Solution

1. Step 1: Understand data lineage concept

   Data lineage tracks the origin and flow of data through systems.

2. Step 2: Match with Snowflake purpose

   Snowflake uses lineage to show data source and movement, not storage or encryption.

3. Final Answer:

   To show where data comes from and how it moves -> Option B

4. Quick Check:

   Data lineage = data origin and flow [OK]

Hint: Data lineage means tracking data origin and flow [OK]

Common Mistakes:

• Confusing lineage with storage management
• Thinking lineage is about encryption
• Mixing lineage with user management

2. Which Snowflake command helps you explore data lineage by showing object dependencies?

easy

A. SHOW OBJECT DEPENDENCIES

B. SHOW USERS

C. DESCRIBE TABLE

D. CREATE WAREHOUSE

Solution

1. Step 1: Identify command for lineage

   SHOW OBJECT DEPENDENCIES lists how objects depend on each other, revealing lineage.

2. Step 2: Eliminate unrelated commands

   SHOW USERS lists users, DESCRIBE TABLE shows table structure, CREATE WAREHOUSE creates compute resources.

3. Final Answer:

   SHOW OBJECT DEPENDENCIES -> Option A

4. Quick Check:

   Lineage command = SHOW OBJECT DEPENDENCIES [OK]

Hint: Use SHOW OBJECT DEPENDENCIES to see lineage [OK]

Common Mistakes:

• Using SHOW USERS for lineage
• Confusing DESCRIBE TABLE with lineage
• Thinking CREATE WAREHOUSE shows dependencies

3. Given the following Snowflake query:

SHOW OBJECT DEPENDENCIES LIKE 'SALES_DATA';

What does this query return?

medium

A. List of users who accessed SALES_DATA

B. List of warehouses running SALES_DATA queries

C. List of tables with similar names to SALES_DATA

D. List of objects that depend on or are used by SALES_DATA

Solution

1. Step 1: Understand SHOW OBJECT DEPENDENCIES usage

   This command shows dependencies related to the specified object, here SALES_DATA.

2. Step 2: Interpret LIKE filter

   LIKE 'SALES_DATA' filters to objects named SALES_DATA, showing their dependencies.

3. Final Answer:

   List of objects that depend on or are used by SALES_DATA -> Option D

4. Quick Check:

   SHOW OBJECT DEPENDENCIES LIKE = dependency list [OK]

Hint: SHOW OBJECT DEPENDENCIES lists related objects [OK]

Common Mistakes:

• Thinking it shows user access logs
• Confusing with warehouse usage
• Assuming it lists similar table names

4. You run SHOW OBJECT DEPENDENCIES LIKE 'CUSTOMER_ORDERS'; but get no results. What is a likely reason?

medium

A. The object name is misspelled or does not exist

B. You need to create a warehouse first

C. SHOW OBJECT DEPENDENCIES does not work on tables

D. Your user lacks SELECT permission on CUSTOMER_ORDERS

Solution

1. Step 1: Check object existence

   No results usually mean the object name is wrong or missing in the database.

2. Step 2: Verify command applicability and permissions

   SHOW OBJECT DEPENDENCIES works on tables; warehouse creation is unrelated; lack of SELECT permission does not hide dependencies.

3. Final Answer:

   The object name is misspelled or does not exist -> Option A

4. Quick Check:

   No results = wrong or missing object name [OK]

Hint: Check spelling and existence if no dependencies show [OK]

Common Mistakes:

• Assuming warehouse needed for lineage
• Thinking permissions block SHOW OBJECT DEPENDENCIES
• Believing tables can't have dependencies

5. You want to track data lineage for a complex pipeline involving multiple views and tables in Snowflake. Which approach best ensures accurate lineage tracking?

hard

A. Only track lineage for base tables, ignoring views

B. Manually document dependencies in a spreadsheet

C. Use SHOW OBJECT DEPENDENCIES and automate lineage extraction with Snowflake metadata queries

D. Rely on user memory to recall data flow

Solution

1. Step 1: Understand lineage complexity

   Complex pipelines need automated, accurate tracking to avoid errors and omissions.

2. Step 2: Evaluate options for accuracy and scalability

   Manual docs and memory are error-prone; ignoring views misses dependencies; using SHOW OBJECT DEPENDENCIES with automation is best practice.

3. Final Answer:

   Use SHOW OBJECT DEPENDENCIES and automate lineage extraction with Snowflake metadata queries -> Option C

4. Quick Check:

   Automate lineage with SHOW OBJECT DEPENDENCIES for accuracy [OK]

Hint: Automate lineage extraction using SHOW OBJECT DEPENDENCIES [OK]

Common Mistakes:

• Relying on manual documentation only
• Ignoring views in lineage tracking
• Trusting memory instead of tools