Question 1

You are building a data pipeline that uses Amazon Kinesis Data Streams for real-time data ingestion. What is the most cost-effective way to process this streaming data?

A. Use Amazon EC2 instances to process the data in real-time
B. Use AWS Lambda to process the data in real-time
C. Use AWS Glue to process the data in real-time
D. Use Amazon Redshift to process the data in real-time

✅ Answer: B. Use AWS Lambda to process the data in real-time
📘 Explanation: AWS Lambda is a serverless compute service that allows you to process streaming data without provisioning servers. It is cost-effective since you only pay for the compute time you use.

Question 2

You need to store large amounts of structured data for batch processing in AWS. Which storage service is the most cost-effective for this use case?

A. Amazon S3
B. Amazon EBS
C. Amazon RDS
D. Amazon DynamoDB

✅ Answer: A. Amazon S3
📘 Explanation: Amazon S3 is a highly scalable object storage service ideal for storing large amounts of data in a cost-effective manner. It is suitable for batch processing, especially with tools like AWS Glue, Amazon EMR, and Amazon Athena.

Question 3

Which AWS service would you use to analyze large-scale datasets using SQL queries, without managing any infrastructure?

A. Amazon EC2
B. Amazon Athena
C. AWS Glue
D. Amazon RDS

✅ Answer: B. Amazon Athena
📘 Explanation: Amazon Athena is an interactive query service that allows you to analyze data directly in Amazon S3 using standard SQL queries. It is serverless, so you do not need to manage any infrastructure.

Question 4

You have an application that generates a large number of log files in real-time. These log files are stored in Amazon S3. You need to quickly process and analyze the logs to identify patterns. Which AWS service is best suited for this?

A. Amazon Redshift
B. AWS Lambda
C. Amazon EMR
D. Amazon Kinesis Data Analytics

✅ Answer: D. Amazon Kinesis Data Analytics
📘 Explanation: Amazon Kinesis Data Analytics allows you to process real-time data streams using SQL. It is an excellent choice for analyzing log data stored in Amazon S3 and identifying patterns in real-time.

Question 5

You need to implement a solution for real-time analytics on streaming data in AWS. Which service can be used to ingest and process the data?

A. Amazon S3
B. Amazon Kinesis
C. Amazon CloudWatch
D. Amazon Redshift

✅ Answer: B. Amazon Kinesis
📘 Explanation: Amazon Kinesis is designed for real-time data streaming. It offers services like Kinesis Data Streams, Kinesis Data Firehose, and Kinesis Data Analytics to ingest and process streaming data.

Question 6

Which of the following AWS services is designed to simplify the ETL (Extract, Transform, Load) process for large-scale data processing?

A. Amazon Athena
B. AWS Glue
C. Amazon Redshift
D. AWS Lambda

✅ Answer: B. AWS Glue
📘 Explanation: AWS Glue is a fully managed ETL service that makes it easy to prepare and load data for analytics. It can crawl your data sources, discover schema, and perform transformations on your data.

Question 7

You need to analyze structured and unstructured data in Amazon S3. Which service would you use to run SQL queries on the data?

A. Amazon Athena
B. Amazon EMR
C. AWS Glue
D. Amazon RDS

✅ Answer: A. Amazon Athena
📘 Explanation: Amazon Athena is a serverless interactive query service that allows you to run SQL queries directly on data stored in Amazon S3, supporting both structured and unstructured data formats.

Question 8

You have a large data set stored in Amazon S3 and need to run distributed processing jobs. Which AWS service should you use?

A. AWS Glue
B. Amazon EMR
C. Amazon RDS
D. Amazon Kinesis

✅ Answer: B. Amazon EMR
📘 Explanation: Amazon EMR is a cloud-native big data platform that allows you to run distributed processing jobs using Apache Spark, Hadoop, and other big data frameworks on large datasets stored in Amazon S3.

Question 9

You are working with a large data warehouse and need to load large amounts of structured data efficiently into Amazon Redshift. Which method should you use?

A. Load data directly from Amazon S3 using COPY commands
B. Use AWS Lambda to load data in small batches
C. Use AWS Glue to load data in real-time
D. Load data directly from Amazon RDS

✅ Answer: A. Load data directly from Amazon S3 using COPY commands
📘 Explanation: Amazon Redshift’s COPY command is optimized for loading large amounts of structured data from Amazon S3. It is the most efficient method for batch loading into Redshift.

Question 10

Which AWS service helps in transforming data into actionable insights by allowing you to visually represent metrics and KPIs?

A. Amazon QuickSight
B. Amazon Athena
C. AWS Lambda
D. Amazon S3

✅ Answer: A. Amazon QuickSight
📘 Explanation: Amazon QuickSight is a scalable, serverless business intelligence (BI) service that allows you to visualize data, perform analytics, and create reports and dashboards from multiple data sources.

Question 11

You need to run complex data processing workflows in AWS. Which service allows you to manage, run, and automate these workflows?

A. AWS Lambda
B. AWS Step Functions
C. Amazon S3
D. Amazon Kinesis

✅ Answer: B. AWS Step Functions
📘 Explanation: AWS Step Functions allows you to coordinate and manage distributed applications and workflows in AWS, helping to automate complex processing tasks.

Question 12

You have data stored in Amazon S3, and you want to find insights in the data without moving it. Which service allows you to run SQL queries on the data directly in S3?

A. Amazon Redshift
B. Amazon RDS
C. Amazon Athena
D. AWS Glue

✅ Answer: C. Amazon Athena
📘 Explanation: Amazon Athena is a serverless service that enables you to query data directly from Amazon S3 using standard SQL without needing to move the data into another service.

Question 13

Which AWS service allows you to create and run SQL queries on data in Amazon Redshift?

A. Amazon Athena
B. Amazon QuickSight
C. Amazon S3
D. Amazon Redshift Spectrum

✅ Answer: D. Amazon Redshift Spectrum
📘 Explanation: Amazon Redshift Spectrum allows you to run SQL queries on data in Amazon S3 without needing to load it into Amazon Redshift, making it ideal for analyzing data directly in the cloud.

Question 14

You need to provide a real-time streaming solution for processing large amounts of log data. Which AWS service would you use?

A. Amazon Redshift
B. Amazon Kinesis Data Streams
C. AWS Lambda
D. Amazon S3

✅ Answer: B. Amazon Kinesis Data Streams
📘 Explanation: Amazon Kinesis Data Streams is a real-time data streaming service that allows you to collect and process large amounts of streaming data such as log files, metrics, and social media feeds.

Question 15

Which AWS service is specifically designed to handle batch processing of large datasets, running Hadoop and Spark workloads?

A. Amazon S3
B. AWS Glue
C. Amazon EMR
D. Amazon QuickSight

✅ Answer: C. Amazon EMR
📘 Explanation: Amazon EMR is a cloud-native big data platform that allows you to process large datasets in batch using Hadoop, Apache Spark, and other big data frameworks.

Question 16

Which of the following is the most cost-effective service for processing large amounts of data stored in Amazon S3 in a serverless manner?

A. Amazon Kinesis
B. AWS Lambda
C. AWS Glue
D. Amazon RDS

✅ Answer: B. AWS Lambda
📘 Explanation: AWS Lambda is a cost-effective, serverless compute service that can process large datasets stored in Amazon S3 based on events, and you only pay for the compute time consumed.

Question 17

Which AWS service can be used to automate the extraction, transformation, and loading (ETL) processes for structured and semi-structured data?

A. AWS Glue
B. Amazon Redshift
C. Amazon Athena
D. Amazon Kinesis

✅ Answer: A. AWS Glue
📘 Explanation: AWS Glue is a fully managed ETL service that automates the process of extracting data from various sources, transforming it, and loading it into target data stores such as Amazon Redshift or Amazon S3.

Question 18

Which of the following services enables near real-time analysis of streaming data?

A. Amazon S3
B. Amazon Redshift
C. Amazon Kinesis Data Analytics
D. Amazon EC2

✅ Answer: C. Amazon Kinesis Data Analytics
📘 Explanation: Amazon Kinesis Data Analytics allows you to analyze streaming data in real time using SQL, making it suitable for use cases like log analytics and clickstream analysis.

Question 19

What is the most cost-effective way to store large amounts of historical data that you want to keep indefinitely but only access occasionally?

A. Amazon S3 Standard
B. Amazon S3 Glacier
C. Amazon EBS
D. Amazon RDS

✅ Answer: B. Amazon S3 Glacier
📘 Explanation: Amazon S3 Glacier is a low-cost storage class designed for archival data that is infrequently accessed, offering significant savings compared to other S3 storage classes.

Question 20

You need to store and analyze large amounts of time-series data. Which AWS service is specifically built for this purpose?

A. Amazon Kinesis Data Streams
B. Amazon Timestream
C. Amazon RDS
D. AWS Lambda

✅ Answer: B. Amazon Timestream
📘 Explanation: Amazon Timestream is a time-series database designed to efficiently store and analyze time-stamped data, making it ideal for use cases like IoT, monitoring, and log analytics.

Question 21

You are managing a data lake on AWS using Amazon S3. You need to provide fine-grained access control to the objects stored in S3 based on specific user roles. What is the most effective method to achieve this?

A. Use AWS Identity and Access Management (IAM) policies
B. Use Amazon S3 Bucket Policies
C. Use AWS Lambda to control access
D. Use Amazon S3 Access Control Lists (ACLs)

✅ Answer: A. Use AWS Identity and Access Management (IAM) policies
📘 Explanation: IAM policies allow you to define permissions based on user roles, making it the most effective method for managing fine-grained access control for Amazon S3 objects.

Question 22

Which AWS service can be used to analyze large volumes of unstructured data stored in Amazon S3 without having to move the data?

A. Amazon RDS
B. Amazon EMR
C. Amazon Athena
D. AWS Glue

✅ Answer: C. Amazon Athena
📘 Explanation: Amazon Athena allows you to query unstructured data directly in Amazon S3 using SQL, without moving or loading the data elsewhere, making it efficient for quick analysis.

Question 23

You need to provide real-time analytics and insights from a stream of incoming sensor data. Which AWS service would you use?

A. AWS Lambda
B. Amazon S3
C. Amazon Kinesis Data Analytics
D. Amazon EC2

✅ Answer: C. Amazon Kinesis Data Analytics
📘 Explanation: Amazon Kinesis Data Analytics enables real-time processing of streaming data to analyze and gain insights from sensor data, log files, and other real-time sources.

Question 24

Which of the following AWS services is best suited for processing large amounts of log data in real-time?

A. Amazon S3
B. Amazon CloudWatch Logs
C. AWS Lambda
D. Amazon Kinesis Data Streams

✅ Answer: D. Amazon Kinesis Data Streams
📘 Explanation: Amazon Kinesis Data Streams is designed for real-time log and event data ingestion, allowing you to process large volumes of log data in real time.

Question 25

Which service is used to perform extract, transform, and load (ETL) operations on data stored in Amazon S3?

A. AWS Lambda
B. AWS Glue
C. Amazon Kinesis
D. Amazon Redshift

✅ Answer: B. AWS Glue
📘 Explanation: AWS Glue is a fully managed ETL service that can read data from Amazon S3, transform it according to your needs, and load it into data warehouses or other data lakes.