Sample Questions and Answers
What service allows users to stream data into Amazon S3 in real-time?
AWS Lambda
B. Amazon Kinesis Data Firehose
C. Amazon RDS
D. AWS Glue
Answer: B. Amazon Kinesis Data Firehose
Explanation:
Amazon Kinesis Data Firehose is used for real-time streaming data and automatically delivers it to Amazon S3 or other services for storage.
Which AWS service is designed to manage machine learning workflows, including dataset labeling and model versioning?
Amazon SageMaker
B. Amazon Athena
C. Amazon Lex
D. AWS Glue
Answer: A. Amazon SageMaker
Explanation:
Amazon SageMaker is a fully managed service that covers all aspects of the machine learning lifecycle, from dataset preparation and labeling to model deployment.
Which of the following services provides data warehousing capabilities and supports complex queries for large data sets?
Amazon DynamoDB
B. Amazon Redshift
C. Amazon Athena
D. AWS Lambda
Answer: B. Amazon Redshift
Explanation:
Amazon Redshift is a fully managed data warehousing service that allows users to perform complex queries on large datasets efficiently.
Which AWS service helps secure access to big data by identifying and classifying sensitive data in Amazon S3?
Amazon Macie
B. AWS Lambda
C. Amazon CloudWatch
D. Amazon Kinesis
Answer: A. Amazon Macie
Explanation:
Amazon Macie uses machine learning to automatically discover, classify, and protect sensitive data stored in Amazon S3.
What AWS service allows users to store and manage large amounts of unstructured data such as logs, backups, and archives?
Amazon S3
B. Amazon RDS
C. Amazon DynamoDB
D. AWS Lambda
Answer: A. Amazon S3
Explanation:
Amazon S3 is an object storage service that allows you to store large amounts of unstructured data, including logs, backups, and archives.
Which AWS service provides real-time analytics on streaming data without needing to provision infrastructure?
Amazon Kinesis Data Analytics
B. Amazon Athena
C. Amazon QuickSight
D. Amazon EMR
Answer: A. Amazon Kinesis Data Analytics
Explanation:
Amazon Kinesis Data Analytics enables real-time analytics on streaming data, allowing users to run SQL queries on live data streams without managing infrastructure.
What service would you use for machine learning-powered insights from unstructured data like text, audio, or images?
Amazon Kinesis
B. AWS Comprehend
C. AWS Glue
D. Amazon S3
Answer: B. AWS Comprehend
Explanation:
AWS Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text data.
Which service is primarily used for batch processing large data sets in AWS?
Amazon EC2
B. AWS Glue
C. Amazon S3
D. Amazon EMR
Answer: D. Amazon EMR
Explanation:
Amazon EMR is designed for processing large data sets in batch mode using frameworks like Hadoop and Spark.
What service enables users to create a scalable, cost-effective, and secure data lake in AWS?
Amazon Redshift
B. AWS Lake Formation
C. AWS Glue
D. Amazon S3
Answer: B. AWS Lake Formation
Explanation:
AWS Lake Formation simplifies the process of setting up and managing secure data lakes using Amazon S3 and other AWS services.
Which AWS service would be most appropriate for analyzing real-time clickstream data from a website?
Amazon Kinesis
B. Amazon Redshift
C. Amazon Athena
D. AWS Glue
Answer: A. Amazon Kinesis
Explanation:
Amazon Kinesis is ideal for collecting and analyzing real-time data streams, such as clickstream data, to gain insights and take immediate action.
Which AWS service provides a simple way to deploy and manage Docker containers for big data workloads?
Amazon ECS
B. AWS Lambda
C. Amazon EMR
D. Amazon EC2
Answer: A. Amazon ECS
Explanation:
Amazon ECS (Elastic Container Service) allows you to deploy and manage Docker containers at scale, making it a great choice for big data workloads that require containerized applications.
Which service in AWS allows users to analyze structured and unstructured data with SQL-like queries directly on data stored in S3?
Amazon Redshift
B. Amazon Athena
C. AWS Glue
D. Amazon RDS
Answer: B. Amazon Athena
Explanation:
Amazon Athena allows users to run SQL queries directly on data stored in Amazon S3 without the need to load or transform the data first.
What service can be used to automate the collection and processing of data across AWS services for analytics?
AWS Glue
B. Amazon Redshift
C. Amazon QuickSight
D. Amazon S3
Answer: A. AWS Glue
Explanation:
AWS Glue automates the extraction, transformation, and loading (ETL) of data, making it easier to collect and process data from various AWS services for analytics.
Which service provides a fully managed Hadoop ecosystem for processing big data workloads on AWS?
Amazon EMR
B. AWS Lambda
C. Amazon S3
D. AWS Glue
Answer: A. Amazon EMR
Explanation:
Amazon EMR (Elastic MapReduce) provides a fully managed Hadoop ecosystem for processing large-scale data in a distributed fashion.
Which of the following services is most suitable for performing ad-hoc queries on structured data stored in Amazon S3?
Amazon Redshift
B. Amazon Athena
C. Amazon RDS
D. Amazon DynamoDB
Answer: B. Amazon Athena
Explanation:
Amazon Athena is an interactive query service that allows you to run SQL queries directly on data stored in Amazon S3.
Which service is best suited for real-time analytics on data streams, such as financial transactions?
AWS Glue
B. Amazon Kinesis Data Analytics
C. Amazon S3
D. Amazon Redshift
Answer: B. Amazon Kinesis Data Analytics
Explanation:
Amazon Kinesis Data Analytics enables real-time analytics and processing of data streams, which is ideal for analyzing financial transactions.
Which AWS service is designed to handle large-scale data processing for machine learning workflows in the cloud?
Amazon SageMaker
B. AWS Lambda
C. Amazon EC2
D. Amazon Elastic File System (EFS)
Answer: A. Amazon SageMaker
Explanation:
Amazon SageMaker is a fully managed service designed for building, training, and deploying machine learning models at scale.
What is the primary benefit of using Amazon Redshift Spectrum?
It enables querying data in Amazon DynamoDB
B. It allows querying data directly in Amazon S3
C. It integrates with AWS Glue for data preparation
D. It allows automated scaling of data storage
Answer: B. It allows querying data directly in Amazon S3
Explanation:
Redshift Spectrum allows you to run queries on data stored in Amazon S3 without needing to load the data into Amazon Redshift first.
What service can you use to process and store large, unstructured datasets like logs and social media content?
Amazon DynamoDB
B. Amazon RDS
C. Amazon S3
D. Amazon Redshift
Answer: C. Amazon S3
Explanation:
Amazon S3 is ideal for storing unstructured data such as logs, videos, images, and social media content due to its scalable, low-cost storage capabilities.
Which AWS service provides real-time data ingestion, buffering, and delivery to other services for further processing?
Amazon Kinesis Data Streams
B. AWS Glue
C. Amazon RDS
D. Amazon Redshift
Answer: A. Amazon Kinesis Data Streams
Explanation:
Amazon Kinesis Data Streams is a real-time data ingestion service that allows you to capture, buffer, and process streaming data.
Which AWS service provides a fully managed, scalable, and secure message queuing system for big data processing?
Amazon SQS
B. AWS Lambda
C. Amazon SNS
D. Amazon Kinesis
Answer: A. Amazon SQS
Explanation:
Amazon SQS (Simple Queue Service) is a fully managed message queuing service that helps decouple and scale microservices, distributed systems, and big data workloads.
What is the primary purpose of AWS Glue DataBrew?
To automate ETL processes
B. To build data pipelines
C. To prepare and clean data for analytics
D. To manage data lakes
Answer: C. To prepare and clean data for analytics
Explanation:
AWS Glue DataBrew is a visual data preparation tool that allows data engineers and analysts to clean and prepare data for analysis.
Which AWS service allows you to analyze data using SQL queries directly on Amazon S3 without needing to set up a database?
Amazon RDS
B. Amazon DynamoDB
C. Amazon Athena
D. Amazon Kinesis
Answer: C. Amazon Athena
Explanation:
Amazon Athena allows users to run SQL queries directly on data stored in Amazon S3, making it an excellent tool for querying large datasets without the need to set up a database.
Which AWS service enables you to track and analyze the lineage of data as it moves across your data lake?
AWS Data Catalog
B. AWS Glue
C. Amazon S3
D. Amazon QuickSight
Answer: A. AWS Data Catalog
Explanation:
AWS Glue Data Catalog is a central metadata repository that tracks and analyzes the lineage of data stored in a data lake, enabling better governance and management.
Which of the following services can be used to store large data sets in a secure and cost-effective manner for big data analytics?
Amazon RDS
B. Amazon DynamoDB
C. Amazon Redshift
D. Amazon S3
Answer: D. Amazon S3
Explanation:
Amazon S3 is a cost-effective, scalable, and secure service for storing large amounts of data, making it ideal for big data analytics workloads.
What service allows you to build and train machine learning models on large data sets in the cloud?
Amazon SageMaker
B. AWS Lambda
C. AWS Glue
D. Amazon Kinesis
Answer: A. Amazon SageMaker
Explanation:
Amazon SageMaker is designed to help build, train, and deploy machine learning models at scale, leveraging AWS’s computational power and infrastructure.
Which service can you use to perform real-time analytics on unstructured text data from social media or documents?
Amazon Comprehend
B. AWS Lambda
C. Amazon S3
D. Amazon QuickSight
Answer: A. Amazon Comprehend
Explanation:
Amazon Comprehend uses natural language processing (NLP) to analyze unstructured text data from various sources like social media and documents to extract valuable insights.
Which of the following AWS services is most appropriate for preparing and transforming large-scale datasets for analysis?
AWS Glue
B. Amazon DynamoDB
C. Amazon RDS
D. Amazon Redshift
Answer: A. AWS Glue
Explanation:
AWS Glue is a fully managed ETL service that prepares, cleanses, and transforms large datasets for analytics or machine learning.
Which service is commonly used to automate the process of loading, transforming, and cleaning data from various sources for a data warehouse?
AWS Lambda
B. AWS Glue
C. Amazon EMR
D. Amazon Redshift
Answer: B. AWS Glue
Explanation:
AWS Glue automates the ETL (Extract, Transform, Load) process to load and prepare data from multiple sources for analysis in a data warehouse like Amazon Redshift.
Which of the following AWS services provides a serverless architecture for big data applications, without the need for provisioning or managing servers?
Amazon EMR
B. AWS Lambda
C. Amazon EC2
D. Amazon Kinesis
Answer: B. AWS Lambda
Explanation:
AWS Lambda is a serverless computing service that automatically manages the infrastructure for your big data applications, so you only focus on the code.
Which AWS service enables fast, interactive SQL queries on large amounts of data stored in Amazon S3 using serverless architecture?
Amazon Redshift Spectrum
B. Amazon Kinesis Data Streams
C. Amazon Athena
D. Amazon QuickSight
Answer: C. Amazon Athena
Explanation:
Amazon Athena allows for fast, serverless SQL queries on large datasets stored in Amazon S3, making it ideal for ad-hoc analytics.
Which of the following services can be used to quickly analyze streaming data and gain insights into your application’s performance?
Amazon CloudWatch
B. Amazon Redshift
C. Amazon Kinesis Data Analytics
D. AWS Glue
Answer: C. Amazon Kinesis Data Analytics
Explanation:
Amazon Kinesis Data Analytics is specifically designed for real-time data stream analytics, enabling insights into streaming data for applications like performance monitoring.
What feature of Amazon Kinesis allows users to process real-time streaming data with minimal latency?
Kinesis Data Streams
B. Kinesis Data Firehose
C. Kinesis Data Analytics
D. Kinesis Video Streams
Answer: A. Kinesis Data Streams
Explanation:
Amazon Kinesis Data Streams allows users to collect and process real-time data streams with minimal latency, enabling real-time analytics.
Reviews
There are no reviews yet.