AWS Certified Data Analytics Specialty 2021 – Hands-On - Kinesis Data Firehose

The video tutorial provides an in-depth overview of AWS Kinesis Data Firehose, explaining its functionality, key destinations, and partner integrations. It covers data transformation and compression capabilities, cost and billing considerations, and compares Firehose with Kinesis Data Streams. The tutorial also delves into buffer sizing and throughput management, highlighting the differences between real-time and near real-time data processing.

What is the primary function of Kinesis Data Firehose?

• To store data in real-time

• To provide data analytics

• To batch write data into target destinations

• To manage data streams

Which of the following is NOT a destination for Kinesis Data Firehose?

• Amazon Redshift

• Amazon S3

• Amazon DynamoDB

• Amazon Elasticsearch

How does Kinesis Data Firehose handle data transformation?

• By manual coding

• Using AWS Lambda functions

• With third-party software

• Through built-in transformation tools

Which compression method is supported by Kinesis Data Firehose when loading data into Redshift?

• gzip

• bzip2

• zip

• snappy

What is the minimum buffer time setting for Kinesis Data Firehose?

• 5 minutes

• 30 seconds

• 1 minute

• 10 minutes

Which service requires custom code for producers and consumers?

• Kinesis Data Firehose

• Kinesis Data Streams

• Amazon S3

• Amazon Redshift

What is a key difference between Kinesis Data Streams and Firehose?

• Firehose supports data replay, Streams do not

• Streams are fully managed, Firehose is not

• Streams require manual scaling, Firehose auto-scales

• Firehose is real-time, Streams is near real-time