The Who, Where, What, How, and When of Snowflake View Types

Snowflake offers several types of views to provide flexibility and control over how data is presented and queried. This guide covers the who, where, what, how, and when of Snowflake view types, helping you choose the right view for your use case.

Who Uses Snowflake View Types?

Snowflake views are utilized by:

• Data Engineers: To create reusable data models for various teams.
• Data Analysts: For simplifying complex queries and focusing on business insights.
• BI Developers: To provide consistent and optimized datasets for dashboards and reports.
• Data Scientists: To access transformed datasets for machine learning workflows.

Where Are Snowflake Views Used?

Snowflake views are applied in:

• Data Warehouses: For creating logical representations of data without duplicating it.
• ETL Workflows: To stage transformed data for downstream processes.
• Reporting Systems: For providing curated datasets for dashboards.
• Data Sharing: To share specific subsets of data securely.

What Are Snowflake View Types?

Snowflake provides three main types of views, each tailored for specific use cases:

1. Standard View

• A basic view that stores only the query definition.
• Characteristics:
  • Always retrieves fresh data by executing the query in real-time.
  • Lightweight and simple to implement.
• Use Case: Ad-hoc queries or views where data freshness is critical.
• Example:

  CREATE VIEW current_sales AS
  SELECT * FROM sales WHERE sales_date = CURRENT_DATE;
  

2. Materialized View

• A view that stores the results of the query physically, allowing faster access.
• Characteristics:
  • Automatically updates when the underlying data changes.
  • Uses additional storage to maintain query results.
• Use Case: High-performance reporting or aggregations on large datasets.
• Example:

  CREATE MATERIALIZED VIEW monthly_sales AS
  SELECT region, SUM(amount) AS total_sales
  FROM sales
  WHERE EXTRACT(MONTH FROM sales_date) = EXTRACT(MONTH FROM CURRENT_DATE)
  GROUP BY region;
  

3. Secure View

• A view that restricts access to the underlying query definition.
• Characteristics:
  • Prevents users from viewing the SQL logic.
  • Provides an additional layer of security for sensitive data.
• Use Case: Sharing views with external users while protecting business logic.
• Example:

  CREATE SECURE VIEW masked_sales AS
  SELECT id, region, 'REDACTED' AS sensitive_data FROM sales;
  

How Do Snowflake Views Work?

1. Creating Views

Views are created using the CREATE VIEW or CREATE MATERIALIZED VIEW commands:

CREATE VIEW simple_view AS
SELECT id, name FROM customers WHERE active = TRUE;

2. Querying Views

Views can be queried like tables:

SELECT * FROM simple_view;

3. Managing Views

• Alter View: Modify an existing view’s definition.

  ALTER VIEW simple_view AS SELECT id, name, email FROM customers WHERE active = TRUE;
  

• Drop View: Remove a view from the database.

  DROP VIEW simple_view;
  

When Should You Use Specific View Types?

1. Standard View

• When: You need a lightweight solution and real-time query results.

2. Materialized View

• When: Performance is critical, and you need precomputed results for large datasets.

3. Secure View

• When: You want to share views securely while hiding query logic.

Best Practices for Snowflake Views

1. Choose the Right View Type:
   • Use materialized views for performance-intensive queries.
   • Use secure views for sharing sensitive data.
2. Monitor Query Performance:
   • Regularly review query execution plans to optimize view definitions.
3. Manage Storage Costs:
   • Be mindful of storage consumption for materialized views.
4. Leverage Secure Views for Governance:
   • Use secure views to enforce data masking and access policies.
5. Test Changes:
   • Validate view modifications in a development environment before deploying.

Conclusion

Snowflake views are powerful tools for abstracting, securing, and optimizing data access. By understanding the different view types and their use cases, you can design efficient and secure data models that align with your business requirements.

Unlock the potential of Snowflake views to simplify your data workflows and enhance collaboration across teams.