Explanation
https://docs.snowflake.com/en/user-guide/privatelink-azure.html

Explanation
Alation provides Data Cataloging functionality. They state they are the 'One Place to Find, Understand, & Govern Data Across an Enterprise.
https://docs.snowflake.com/en/user-guide/ecosystem-all.html

Clustering keys in Snowflake work by sorting the designated columns over time. This process is done in the background and does not block data manipulation language (DML) operations, allowing for normal database operations to continue without interruption. The purpose of clustering keys is to organize the data within micro-partitions to optimize query performance1.
Reference:
[COF-C02] SnowPro Core Certification Exam Study Guide
Snowflake Documentation on Clustering1

Snowflake's Time Travel feature allows users to access historical data within a specific period. This feature supports the restoration of various objects, including databases and schemas, to their previous states. Time Travel can be used for recovering dropped objects, undoing accidental changes, or analyzing data changes over time. However, it does not support user or role objects like Users and Roles, or compute resources like Virtual Warehouses.
References: Snowflake Documentation on Time Travel

In Snowflake, when dealing with semi-structured data such as a JSON document stored in a VARIANT column, the proper syntax to extract a value is to use the column name followed by the path to the specific element. Since arrays in JSON are zero-indexed, the first element is referenced with [0]. Therefore, to extract the name from the first element of the elements array, the correct syntax is Source_column:elements[0].name.
Reference: Snowflake Documentation on Semi-Structured Data