AWS Certified Cloud Practitioner (CLF-C01)- Amazon Kinesis

The video tutorial provides an overview of Amazon Kinesis, a service for ingesting, processing, and analyzing streaming data. It covers four main components: Kinesis Data Streams, Firehose, Data Analytics, and Video Streams. Each component is explained with its use cases, such as real-time data processing, data delivery to AWS services, SQL-based analytics, and video data handling. The tutorial also includes examples like Uber's use of geospatial data and the integration of machine learning for video analytics.

What is a primary use case of Amazon Kinesis as mentioned in the introduction?

• Data archiving

• Offline data storage

• Real-time data ingestion and analysis

• Batch processing of data

Which of the following is a feature of Amazon Kinesis Data Streams?

• Real-time data analytics

• Batch data processing

• Data archiving

• Data encryption at rest

What is a typical use case for Amazon Kinesis Data Streams?

• Offline data storage

• Real-time metrics and reporting

• Batch processing

• Data archiving

What is a key feature of Amazon Kinesis Firehose?

• Real-time video streaming

• Batch data compression and transformation

• Data encryption at rest

• Offline data storage

Which destination can Amazon Kinesis Firehose deliver data to?

• Amazon RDS

• Amazon S3

• Amazon Glacier

• Amazon CloudFront

What can Amazon Kinesis Data Analytics be used for?

• Data archiving

• Offline data storage

• Real-time SQL-based data processing

• Batch processing of data

What is a capability of Amazon Kinesis Video Streams?

• Real-time SQL-based data processing

• Secure video streaming from connected devices

• Batch data processing

• Data archiving