See why hundreds of industry leaders trust Secoda to unlock their data's full potential.
See why hundreds of industry leaders trust Secoda to unlock their data's full potential.
Get the guideA Snowflake masking policy is an advanced security feature available in the Enterprise Edition or higher of Snowflake. It allows administrators to define and enforce rules to mask or tokenize sensitive data within table columns or views. By applying these policies, organizations can control how sensitive information is displayed to users based on their roles or access levels. This ensures compliance with data protection regulations and enhances overall data security. For example, integrating masking policies with role-based access control in Snowflake ensures that only authorized users can view unmasked data.
The masking policy works dynamically, meaning the data remains unaltered in storage but is transformed on-the-fly when queried. This approach ensures that authorized users can access unmasked data while others see a masked or obfuscated version. Snowflake masking policies are highly customizable, enabling organizations to tailor them to meet specific security requirements.
Creating a masking policy in Snowflake involves defining a set of rules that dictate how data should be masked or transformed. These rules are implemented using the CREATE MASKING POLICY command. Each policy specifies the conditions under which sensitive data is either displayed in its original form or masked. By aligning masking policies with warehouse creation strategies in Snowflake, organizations can improve their overall data governance approach.
The process requires careful planning to ensure that the policy aligns with organizational security standards and regulatory requirements. Below are the key components and syntax for creating a masking policy:
EXEMPT_OTHER_POLICIES property provide flexibility in defining the policy.Here is an example of a simple masking policy that masks email addresses for all users except those with the 'ANALYST' role:
CREATE MASKING POLICY email_mask
AS (val STRING)
RETURNS STRING ->
CASE
WHEN current_role() IN ('ANALYST') THEN val
ELSE '*********'
END;
In this example, users with the 'ANALYST' role can see the full email address, while others see a masked version represented by asterisks.
After creating a masking policy, it must be applied to specific columns in tables or views. This ensures that the policy's rules are enforced whenever the data is accessed. For instance, using masking policies with external tables in Snowflake can extend data security to external datasets while maintaining centralized governance.
To apply a masking policy to a column, use the ALTER TABLE or ALTER VIEW command. For example:
ALTER TABLE employee
MODIFY COLUMN email
SET MASKING POLICY email_mask;
This command associates the email_mask policy with the email column in the employee table. The policy will now govern how the data in this column is displayed based on user roles.
Use the GET_DDL function to view the definition of an existing masking policy.
The DESCRIBE MASKING POLICY command provides details about a policy, including its configuration and associated columns.
Proper privileges such as APPLY MASKING POLICY or OWNERSHIP are required to manage masking policies effectively.
Access control is a critical aspect of managing masking policies in Snowflake. Only authorized users should be allowed to create, modify, or apply these policies to ensure data security and compliance with organizational standards.
Implementing RBAC is a best practice for managing masking policies. This involves creating custom roles with specific privileges and assigning them to users based on their responsibilities. For example:
MASKING_ADMIN for managing masking policies.Dynamic data masking in Snowflake enables real-time protection of sensitive data by applying masking policies to database columns. This feature ensures that data remains unaltered in storage but is transformed dynamically based on the user's role or access level during query execution. For example, combining dynamic masking with Snowflake roles enhances security by tailoring data visibility to user permissions.
ALTER TABLE or ALTER VIEW command to associate the policies with specific columns.Here is an example of a masking policy that displays unmasked data for users in the 'PROD_ACCOUNT' account and masked data for others:
CREATE MASKING POLICY mask_sensitive_data
AS (val STRING)
RETURNS STRING ->
CASE
WHEN current_account() = 'PROD_ACCOUNT' THEN val
ELSE 'MASKED'
END;
This policy ensures that only users in the production account can see the full data, while others see a masked version.
Snowflake masking policies provide significant advantages for data security, but they also pose challenges that must be addressed for successful implementation.
Secoda is a cutting-edge data management platform designed to centralize and streamline data discovery, lineage tracking, governance, and monitoring across an organization's data stack. By acting as a "second brain" for data teams, Secoda enables users to easily find, understand, and trust their data through features like search, data dictionaries, and lineage visualization. This ultimately improves data collaboration and operational efficiency within teams.
With Secoda, organizations can achieve a single source of truth for their data, making it accessible and understandable for both technical and non-technical users. Its AI-powered tools enhance data understanding and simplify complex data processes, ensuring teams can focus on analysis and decision-making rather than searching for information.
Secoda enhances data accessibility and collaboration by providing tools that cater to both technical and non-technical users. Its intuitive interface and natural language search capabilities make it easier for anyone to locate and understand the data they need. Additionally, collaboration features allow teams to document, share, and govern data assets effectively, fostering better teamwork and communication.
By leveraging these features, Secoda empowers teams to work together more efficiently, reducing silos and improving data-driven decision-making.
Secoda offers a comprehensive solution for organizations looking to improve data accessibility, governance, and collaboration. With its AI-powered insights and intuitive tools, you can streamline your data processes and focus on what truly matters—making impactful decisions. Get started today and experience the difference Secoda can make for your data operations.
Built for data teams, designed for everyone so you can get more from your data stack.
© 2025 Secoda, Inc. All rights reserved.
By using this website, you accept our Terms of Use and Privacy Policy.
