5_Applying the Amazon Well-Architected Framework to the Data Pipeline

Flashcards covering key vocabulary related to applying the AWS Well-Architected Framework and Data Analytics Lens to data pipelines.

What is the AWS Well-Architected Framework, and how does it relate to data pipelines?

A framework providing best practices for designing, operating, and evolving cloud-based systems, including data pipelines, ensuring they are secure, reliable, and efficient.

What does the Data Analytics Lens provide?

An approach for reviewing data analytics solutions, including defining the workload, prioritizing pillars, implementing best practices, and continuous evaluation to ensure alignment with business goals and effective data utilization.

What is the Principle of Least Privilege, and why is it important?

A security best practice of granting users only the minimum levels of access necessary to perform their job functions, reducing the risk of unauthorized data access or modification and enhancing overall security.

What is the Performance Efficiency Pillar focused on?

Identifying and selecting solutions that best suit specific technical challenges, optimizing for performance and resource utilization, and ensuring efficient data processing and analysis workflows.

What is involved in the Cost Optimization Pillar?

Managing costs over time by removing unused resources, optimizing infrastructure, and avoiding overprovisioning to ensure efficient spending and maximize the value derived from data analytics investments.

What are Amazon S3 Lifecycle Configurations used to do?

Automate the process of deleting data after a specified period, helping to manage storage costs effectively by transitioning data to cheaper storage tiers or removing it entirely based on predefined rules.

What does the Reliability Pillar entail?

Understanding the business requirements of analytics and ETL jobs to ensure consistent and dependable data processing and availability, minimizing downtime and ensuring data integrity.

What considerations are involved in choosing between ETL and ELT?

Selecting an approach based on business requirements and the nature of the data, considering factors like data volume, complexity, and security requirements to optimize data processing workflows and ensure scalability.