Apply RLS and CLS policies to control data access in Starlake pipelines.
npx skills add https://github.com/starlake-ai/starlake --skill secure
Please help me install this Agent Skill. Skill: secure Source: https://github.com/starlake-ai/starlake/tree/main/.agent/skills/secure Command: npx skills add https://github.com/starlake-ai/starlake --skill secure
Enforce data access controls by applying Row Level Security (RLS) and Column Level Security (CLS) policies within Starlake, preventing unauthorized data exposure.
Run the starlake secure with your target domains and tables to apply the policies.
High-intent search queries and answers about installing and using this skill.
To enforce row level security (RLS) across data pipelines, apply security policies to your target domains and tables using CLI options for access tokens and substitutions, preventing unauthorized data exposure.
Managing column level security (CLS) in a multi-tenant environment involves scoping policies to specific domains and tables, ensuring only authorized users can access restricted columns within your data governance workflows.
Yes, you can integrate access control policy application with existing load and transform workflows to ensure consistent data governance and secure configurable policy application across your datasets.
Applying data governance policies supports CLI options for scheduling and substitutions, allowing configurable and automated policy application across targeted tables and domains.
You need to scope security policies to specific domains and tables when operating multi-tenant data environments, ensuring access control rules precisely target the correct datasets without unauthorized exposure.
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