Column-level security in Snowflake enhances data protection by restricting access and applying masking policies to sensitive data at the column level.
Limiting Access Based on User Privileges:
Column-level security allows administrators to define which users or roles have access to specific columns within a table.
This ensures that sensitive data is only accessible to authorized personnel, thereby reducing the risk of data breaches.
Application of Masking Policies:
Masking policies can be applied to columns to obfuscate sensitive data.
For example, credit card numbers can be masked to show only the last four digits, protecting the full number from being exposed.
Snowflake Documentation: Column-Level Security
Snowflake Documentation: Dynamic Data Masking

A characteristic of a materialized view is that the data accessed through it can be stale.This is because the data in a materialized view may not reflect the latest changes in the base tables until the view is refreshed

The correct answer is C. GET_PATH .
GET_PATH extracts a value from semi-structured data using a path expression. It can be used to access values inside an object, including nested values.
Why C is correct:
For an object stored in a VARIANT or OBJECT column, GET_PATH can retrieve a value by specifying the key path.
Example:
SELECT GET_PATH(src, ' customer.name ' )
FROM my_table;
This accesses the name value inside the customer object.
Why the other options are incorrect:
A). OBJECT_KEYS returns the keys from an object, not the values for a specific key path.
B). OBJECT_PICK returns a new object containing selected key-value pairs, but it is not the general function for accessing a value by path.
D). XMLGET is used for XML data, not general JSON-style object access.
Official Snowflake documentation reference:
Snowflake documentation describes GET_PATH as a function that extracts a value from semi-structured data using a path name.
Reference: Snowflake Documentation - GET_PATH; Querying semi-structured data; SnowPro Core Study Guide - Working with Semi-Structured Data.
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Dynamic Data Masking in Snowflake supports tables and views. These objects can have masking policies applied to their columns to dynamically mask data at query time3.