AWS Certified Data Analytics Specialty 2021 – Hands-On - Collection Section Introduction

The video tutorial covers three main methods of moving data into AWS: real-time, near real-time, and batch collection. Real-time collection allows immediate action on data using services like Kinesis Data Streams, SQS, and IoT. Near real-time collection is more reactive, utilizing tools like Kinesis Data Firehose and Database Migration Service. Batch collection is used for transferring large datasets for historical analysis, employing services such as Snowball and Data Pipeline. The tutorial aims to provide a comprehensive understanding of these methods and their applications.

Which AWS service is used for real-time data collection to perform immediate actions?

• Amazon S3

• Kinesis Data Streams

• AWS Lambda

• Amazon RDS

What is the primary characteristic of near real-time data collection?

• Data storage in cloud

• Batch processing of data

• Reactive action on data

• Immediate action on data

Which service is NOT typically used for near real-time data collection?

• Kinesis Data Firehose

• Amazon S3

• Database Migration Service

• Snowball

What is the main purpose of batch data collection in AWS?

• To migrate databases

• To move large amounts of data for historical analysis

• To store data in real-time

• To perform immediate actions on data

Which AWS service is used for batch data collection?

• AWS Lambda

• Amazon RDS

• Snowball

• Amazon EC2