AWS Certified Data Analytics Specialty 2021 – Hands-On - DynamoDB Streams

The video tutorial explains DynamoDB streams, which track item-level changes in tables, and how they can be integrated with AWS services like Kinesis and Lambda for real-time data processing. It covers the architecture of DynamoDB streams, data management, and the use of Lambda functions to handle stream data. The tutorial also highlights the automatic management of shards by AWS and the importance of enabling streams for capturing updates.

What is the primary purpose of DynamoDB streams?

• To provide backup for DynamoDB tables

• To enhance the security of data

• To capture and log item-level changes

• To store data permanently

Which AWS service can be used to extend the data retention period of DynamoDB streams?

• Amazon S3

• AWS Lambda

• Amazon EC2

• Kinesis Data Streams

How can custom logic be added to process data from DynamoDB streams?

• By implementing a processing layer with Kinesis Client Library or Lambda

• By using AWS S3

• By directly modifying the DynamoDB table

• By using AWS CloudFormation

What is a key feature of DynamoDB streams regarding shard management?

• Shards are not used in DynamoDB streams

• Shards require a separate AWS service

• Shards are automatically managed by AWS

• Shards must be manually provisioned

What is required for a Lambda function to read from a DynamoDB stream?

• A dedicated S3 bucket

• A separate EC2 instance

• An event source mapping and appropriate permissions

• A direct connection to the DynamoDB table