Snowflake - Build and Architect Data Pipelines Using AWS - Lab - Change Tracking Using "Changes"

The video tutorial explains change tracking as a read-only alternative to streams in databases. It covers the implementation of change tracking, including enabling it on tables and querying changes using SQL. The tutorial also compares change tracking with streams, highlighting when to use each method based on data update frequency and consumption needs. The video concludes with a brief mention of building a complete data pipeline.

Describe the process of enabling change tracking on a table.

How can you track changes after ingesting new rows into a table?

What SQL command is used to see both newly ingested and updated rows?

Explain the difference between using 'default' and 'pen only' in the context of change tracking.

What is change tracking and how does it differ from using streams?

When should you choose to use streams instead of change tracking?

What scenarios would lead you to prefer change tracking over streams?