Snowflake - Build and Architect Data Pipelines Using AWS - Data Ingestion – Real-World Use Cases

This video provides a high-level overview of data ingestion into Snowflake, covering both batch and real-time methods. It discusses typical data sources like RDBMS, streaming applications, and REST APIs. The video explains batch data ingestion using staging locations and scheduled jobs, and real-time ingestion using Snowpipe and Kafka connectors. Practical examples are provided to illustrate these concepts.

Which of the following is NOT a typical source of data for ingestion into Snowflake?

• Streaming applications

• REST APIs

• Transaction databases

• Excel spreadsheets

What is the first step in a batch data ingestion pipeline?

• Setting up a Kafka connector

• Extracting data from the source

• Writing data into Snowflake

• Scheduling copy commands

Which storage service is commonly used as a staging location for batch data ingestion?

• Oracle Cloud Storage

• AWS S3

• Azure SQL Database

• Google BigQuery

What triggers a Snowpipe to load data into Snowflake in real-time?

• Manual execution

• Data arrival in the staging location

• A scheduled task

• Completion of a batch job

How can real-time data from Kafka be ingested into Snowflake?

• Via a batch job

• Using a Snowflake task

• Through a REST API

• By setting up a Kafka connector