Snowflake - Build and Architect Data Pipelines Using AWS - Section Overview - Snowflake – Streams and Change Data Captur

The video tutorial covers the concept of Change Data Capture (CDC) and its relationship with streams. It explains different types of streams, data retention, and stillness. The tutorial also delves into change tracking in Snowflake tables and concludes with a mini project that involves implementing an end-to-end pipeline using streams and CDC.

What is the primary purpose of Change Data Capture (CDC) in data management?

• To create new data streams

• To capture and track changes in data

• To enhance data security

• To delete outdated data

Which of the following best describes a stream in the context of data management?

• A static snapshot of data at a point in time

• A tool for data encryption

• A continuous flow of data that can be processed

• A method to store data permanently

What is meant by 'data retention' in the context of streams?

• The process of deleting old data

• The duration for which data is kept in a stream

• The method of encrypting data

• The technique of compressing data

How does change tracking benefit Snowflake tables?

• It improves data visualization

• It reduces data storage costs

• It helps in data encryption

• It allows for real-time data updates

What is the main objective of the mini project discussed in the tutorial?

• To learn about data encryption techniques

• To implement an end-to-end pipeline using streams and CDC

• To explore different types of databases

• To understand data visualization tools