AWS Analytics Workloads: Well-Architected Framework

Which AWS Well-Architected Framework pillar focuses on the ability to run and manage infrastructure as code, automate responses to events, and use data to drive improvements?

Which AWS Well-Architected Framework Lens provides guidance specifically for designing analytics workloads?

What is the primary purpose of using the AWS Well-Architected Framework in the design of data pipelines?

Which of the following is NOT a key element emphasized by the Data Analytics Lens of the AWS Well-Architected Framework?

In the evolution of data architectures, what drove the shift from relational databases in the 1970s to non-relational databases in the 1990s?

What was the primary driver for the evolution from data warehouses to data lakes in the mid-2000s?

What is a defining characteristic of the 'purpose-built cloud data stores' era in the evolution of data architectures?

What challenge led to the development of Lambda architecture and streaming solutions?

Which of the following is a key goal of modern data architectures?

In a modern data architecture on AWS, how is seamless access to a centralized data lake primarily achieved?

Which layer of the Modern Data Architecture pipeline is responsible for matching AWS services to data source characteristics?

What role does a metadata catalog play in the storage layer of a modern data architecture?

In the Modern Data Architecture, how are unstructured, semistructured, and structured data typically stored in the storage layer?

In the context of data zones within Amazon S3 for a Modern Data Architecture, what is the purpose of the 'landing' zone?

Which AWS service is used in the catalog layer to provide schema information for data stored in Amazon S3?

What is the primary role of the processing layer in a modern data architecture pipeline?

Which of the following is NOT a type of data processing supported by the processing layer in a modern data architecture?

What capabilities does the consumption layer introduce to the modern data architecture?

Which of the following components can query data in Amazon S3 directly?

In a streaming analytics pipeline, what is the role of a stream?

Which of the following is typically included in a streaming analytics pipeline?

What happens to the results of streaming analytics processes?

Which AWS service would you use to process a continuous stream of events, such as CloudWatch Events, in near real-time

When designing analytics workloads using the AWS Well-Architected Framework, what is the focus of the 'Cost Optimization' pillar?

In the historical progression of data storage solutions, what characteristic distinguished data lakes from earlier database systems?

In a modern data architecture on AWS, which service enables querying data directly from Amazon S3 using SQL, without requiring data to be loaded into a database?

A data engineer is designing an ingestion pipeline for streaming data from IoT devices. Which AWS service is most appropriate for this use case?

A data architect needs to ensure that all data ingested into their data lake is properly cataloged with metadata. Which AWS service would assist in this task?

Which of the followings pillars of the AWS Well-Architected Framework ensures the confidentiality, integrity, and availability of data?

A company is setting up a modern data architecture where Amazon S3 is used as the primary data lake. Which one of the following strategies should they implement to categorize data in Amazon S3

Which of these services democratizes consumption across the organization by giving unified access to stored data and metadata?

Choose the right Data Analytics Lens guidance decision related elements of data

Choose the right component which is essential in the stream processing pipeline.

A financial company needs to implement a data analytics pipeline to process high-velocity stock market data in real time for fraud detection. The company requires the ability to perform complex event processing and aggregation on the streaming data before storing it for further analysis. Which AWS service best suited for this scenario?

A healthcare organization is building a data lake on AWS to store patient data from various sources, including structured data from relational databases, semi-structured data from medical devices, and unstructured data from clinical notes. The organization wants to enforce consistent data governance policies across the data lake to ensure data quality, security, and compliance with regulatory requirements. Which AWS service is best suited for managing data governance.

A global e-commerce company needs to implement a data analytics solution to analyze customer behavior and personalize recommendations in real time. The company wants to build a highly scalable and fault-tolerant data pipeline to ingest and process clickstream data from millions of users worldwide. Which choice will accomplish that?

A retail company is migrating its on-premises data warehouse to AWS and wants to leverage a combination of structured and unstructured data sources for advanced analytics. The company plans to use Amazon S3 for storing unstructured data and Amazon Redshift for storing structured data. Which services can be used to enable querying across both data sources?

A financial services company is designing architecture for real time fraud for continuous data from bank. Which best solution to protect?

A Data team wants to streamline data to ensure quick data retrieval for analytics, what strategy can they use?

An organization is ingesting large volume of unstructured logs, what AWS pattern will ensure high availability.?