Snowflake - Build and Architect Data Pipelines Using AWS - What Is Row Level Security?

The video tutorial explains row level access policies in Snowflake, using an ecommerce scenario with category managers for sports and music. It highlights the challenges of creating multiple views for each category and introduces role level access policies as a solution. By using mapping tables, access can be controlled based on the admin's role, ensuring secure and efficient data management.

What is the primary focus of row level access policies in Snowflake?

• To optimize database performance

• To encrypt data stored in the database

• To control access to specific rows based on user roles

• To manage data masking at the column level

Why is creating multiple views for each category manager not an ideal solution?

• It does not provide secure access

• It requires significant storage space

• It is time-consuming and difficult to maintain

• It complicates the database schema

What is the role of a mapping table in implementing row level access policies?

• To encrypt sensitive data

• To map user roles to specific data access rules

• To store user credentials

• To backup database tables

How does the mapping table determine which data a sports admin can access?

• By verifying the admin's password

• By comparing the admin's access level with others

• By filtering items where the category is sports

• By checking the admin's login time

What is the benefit of using row level access policies over creating multiple views?

• It increases the speed of data retrieval

• It allows for more complex queries

• It simplifies the process of managing access for many categories

• It reduces the need for data encryption