Hi Rupa,

You can follow below for different approaches for implementing row and column level security

1. ABAC Policies (Attribute-Based Access Control) 

ABAC is the new approach that uses governed tags to centrally enforce security across multiple tables dynamically. You can define policies once at catalog, schema, or table level and it automatically inherits to child objects. Its Tag-driven and it applies dynamically to any table/column matching tag conditions for centralized management across entire scope. You can set 2 types of policies. Row Filter Policies controls which rows users can see. Column Mask Policies redacts or transform column values based on its setup

You must use governed tags (account-level tags with enforced values) and create UDFs (SQL or Python functions) for filter/mask logic. Serverless compute or Runtime 16.4+ is required.

2. Manual Row Filters & Column Masks - Table Based Security

You can apply security directly to individual tables using simple commands. Its simpler for single-table scenarios but doesn't scale well as ABAC. Row filters restrict which rows a user can see in a table. Column Masks control what values a user sees for specific columns

Key difference from ABAC - The manual filters/masks apply to ONE table at a time. ABAC policies apply dynamically across multiple tables based on tags. More details here

3. Dynamic Views - Traditional SQL Based Approach

You can create views with built-in conditional logic using is_account_group_member() type of functions based on the cases. It's used when you want to expose a curated, transformed or joined version of data to users who don't have access to the underlying tables. Its Simple, portable with no special requirements. It's harder to maintain at scale.