AWS Certified Data Analytics Specialty 2021 - Hands-On! - Amazon Web Services (AWS) Data Pipeline

The video tutorial explains AWS Data Pipeline, a web service for scheduling and automating data processing tasks across AWS services like EC2, S3, RDS, DynamoDB, Redshift, and EMR. It covers the basic concept, destinations, features, and activities of Data Pipeline, including task scheduling, precondition checks, and retry mechanisms. The tutorial also discusses using on-premises data and task runners to ensure high availability and reliability in data processing workflows.

What is the primary function of AWS Data Pipeline?

• To schedule and automate data processing tasks

• To manage user access to AWS services

• To provide real-time data analytics

• To store large amounts of data

Which AWS service is NOT mentioned as a destination for AWS Data Pipeline?

• Amazon RDS

• Amazon Redshift

• Amazon S3

• Amazon EC2

What is a precondition check in AWS Data Pipeline?

• A method to ensure data is ready before processing

• A way to back up data

• A tool for visualizing data

• A feature to encrypt data

How can AWS Data Pipeline be used with on-premises data?

• By using AWS Direct Connect

• By using a VPN connection

• By installing a task runner on on-premises machines

• By exporting data to a USB drive

What is the purpose of assigning multiple task runners in AWS Data Pipeline?

• To enhance data security

• To reduce data processing time

• To increase data storage capacity

• To ensure high availability of pipeline activities

Which activity allows AWS Data Pipeline to execute Hive queries?

• Copy activity

• EMR activity

• SQL query activity

• Hive activity

What happens if an activity in AWS Data Pipeline fails after exhausting all retry attempts?

• It sends a success notification

• It deletes the pipeline

• It triggers an on-failure alarm

• It automatically retries indefinitely