AWS Data Engineer Associate - Test 15

The AWS DEA-C01 mock test is a launchpad for your career in data engineering. It validates your AWS knowledge and demonstrates initiative. Yet, certifications alone don’t secure jobs. Employers want candidates who can combine AWS with Power BI, Tableau, SQL, and SAS, while also mastering data engineering platforms like Snowflake, Databricks, and PySpark. Data science and AI skills—TensorFlow, PyTorch, LLMs, and Generative AI—are equally vital. Project work is the ultimate proof of employability.

The SynergisticIT Data Science Job Placement Program ensures your launchpad leads to career success by combining certification-level knowledge with advanced training and projects. Learn more through the SynergisticIT Job Placement Program.

Welcome to your AWS Data Engineer Associate – Test-15

Name

Phone

Q1. An AWS data pipeline using Amazon Redshift is experiencing slower query response times than usual. What is the first action the data engineer should take to identify the cause of the slowdown?

Select 1 option(s):

Review the Amazon Redshift query execution plans to identify inefficient queries.

Increase the size or number of nodes in the Amazon Redshift cluster.

Check the CPU utilization metrics in Amazon CloudWatch for the Redshift cluster.

Examine network bandwidth usage to see if there‘s congestion impacting Redshift performance.

Q2. You are part of a data engineering team responsible for managing a complex data pipeline on AWS. You need to ensure that the infrastructure and resources for the pipeline are created and updated consistently across multiple environments (development, staging, production). Which approach allows you to achieve this consistency and automation by defining your infrastructure as code and using templates to provision resources?

Select 1 option(s):

Manual provisioning

AWS Glue Jobs

Infrastructure as Code (IaC) with AWS CDK

AWS Data Pipeline

Q3. A company is looking for a solution to efficiently unload data from Amazon Redshift to Amazon S3 in a structured format for long-term storage and analysis. Which method should the company use to achieve this?

Select 1 option(s):

Use the UNLOAD command in Amazon Redshift to export data to S3.

Write custom scripts in Python to extract and upload data to S3.

Manually export data from Redshift to CSV files and upload them to S3.

Use AWS Glue ETL jobs to move data from Redshift to S3.

Q4. A data analyst is using Amazon Athena to analyze web traffic data stored in Amazon S3. The requirement is to create a persistent summary view that aggregates daily traffic data by region. Which approach should the analyst use in Athena to achieve this?

Select 1 option(s):

Use a CREATE TABLE AS SELECT (CTAS) statement to aggregate and store the data in a new table.

Implement an AWS Lambda function to preprocess the data in S3 before querying with Athena.

Apply a CREATE VIEW statement in Athena to create a summary view of the daily traffic by region.

Configure AWS Glue DataBrew to aggregate the data and then query the results with Athena.

Q5. An online media company stores a vast amount of video content. New content is accessed frequently, but older content is only occasionally accessed. The company seeks a cost-effective storage solution that aligns with this lifecycle. What storage strategy should they adopt?

Select 1 option(s):

Store all video content in Amazon S3 Glacier.

Use Amazon S3 Standard for new content and transition to S3 Standard-Infrequent Access (IA) for older content.

Maintain all content in Amazon EBS for constant availability.

Utilize Amazon RDS for storing all video content.

Q6. Your team is responsible for managing a complex AWS data infrastructure that includes multiple resources like Amazon S3 buckets, Amazon Redshift clusters, and AWS Glue ETL jobs. You want to ensure that the infrastructure is defined as code and can be consistently provisioned and updated across different environments. Which AWS service allows you to achieve this goal by defining your infrastructure as code using JSON or YAML templates?

Select 1 option(s):

AWS Lambda

AWS Glue

AWS Cloud Development Kit (AWS CDK)

AWS CloudFormation

Q7. A data analyst is using Athena notebooks with Apache Spark to explore a large dataset stored in Amazon S3. The dataset is in CSV format and contains complex nested structures. The analyst needs to flatten the data for easier analysis. What should be the first step in the Athena notebook using Spark?

Select 1 option(s):

Use a Spark SQL CREATE TABLE statement to import the CSV data into a flat table structure.

Execute a PySpark script in the notebook to read the CSV file and flatten the nested structures.

Configure an AWS Glue ETL job to preprocess the data and flatten the structure before analysis.

Apply an Amazon Athena query in the notebook to convert the CSV data to a JSON format.

Q8. A data engineer is optimizing an Amazon Redshift data warehouse to improve query performance. The data warehouse contains large tables with historical data. Which of the following practices should the engineer implement to enhance query performance?

Select 1 option(s):

Increase the number of Redshift nodes to enhance computational power.

Implement sort keys and distribution styles to optimize data storage and retrieval.

Store frequently accessed data in Amazon S3 and query it using Amazon Athena.

Use Amazon QuickSight instead of Redshift for data querying and analysis.

Q9. A company is using Amazon S3 to store important data, and they want to ensure that they can recover previous versions of objects if needed. Which AWS service or feature should they enable for this purpose?

Select 1 option(s):

Amazon S3 Object Lock

Amazon S3 Versioning

Amazon S3 Lifecycle policies

Amazon S3 Multipart Uploads

Q10. A financial institution is required to retain customer transaction records for seven years and make them available for auditing during this period. What is the most suitable AWS service or feature for managing these records?

Select 1 option(s):

Use Amazon S3 with lifecycle policies to transition records to Amazon S3 Glacier after one year.

Store the records in Amazon RDS and regularly create manual backups.

Configure Amazon Redshift to store transaction records and archive them using Spectrum.

Use Amazon EBS volumes to store records and manually move older data to an S3 bucket.

Q11. A company hosts a critical database on Amazon RDS for MySQL to support its e-commerce platform. To ensure data resiliency and availability, which AWS service or feature should the company implement?

Select 1 option(s):

Use Amazon S3 to regularly back up the database.

Enable Multi-AZ (Availability Zone) deployment for the Amazon RDS instance.

Store database backups in Amazon Redshift for fast recovery.

Use Amazon Elastic Block Store (EBS) snapshots for backup.

Q12. You are working on a data processing application that needs to efficiently search for specific items in a large dataset. The dataset is organized as a hierarchical structure with parent and child nodes. Which data structure is best suited for this scenario?

Select 1 option(s):

Arrays

Stacks

Trees

Hash Tables

Q13. A company stores large datasets in Amazon S3, partitioned by date and region. They need to ensure that their Amazon Athena queries always access the most current data without manual updates to the data catalog. Which method should they use to synchronize their data catalog with the partitioned data in S3?

Select 1 option(s):

Use AWS Data Pipeline to update the data catalog.

Implement AWS Glue Crawlers to automatically update the data catalog.

Manually update the data catalog using Amazon Athena.

Configure Amazon Redshift Spectrum for data synchronization.

Q14. A company is using Amazon EMR for big data processing and has integrated it with AWS Lake Formation for enhanced data security and governance. They want to ensure that specific data analysts have access to only certain datasets managed by Lake Formation. How should they configure permissions to achieve this?

Select 1 option(s):

Implement Network Access Control Lists (NACLs) to restrict EMR cluster access to specific datasets.

Grant permissions using IAM policies attached to the data analysts‘ IAM roles for accessing specific datasets in Lake Formation.

Use Lake Formation to define and grant fine-grained data access permissions for the data analysts on the specific datasets.

Store datasets in separate Amazon S3 buckets and use S3 bucket policies to control access by the data analysts.

Q15. A company is storing sensitive financial data in Amazon S3 and requires that the data is encrypted at rest. They want to ensure that they maintain control over the encryption keys used. Which AWS service should they use for managing these encryption keys?

Select 1 option(s):

Use Amazon S3 server-side encryption with Amazon-managed keys (SSE-S3).

Implement AWS Key Management Service (AWS KMS) to create and manage their own encryption keys.

Enable Amazon S3 server-side encryption with customer-provided keys (SSE-C).

Apply Amazon Cognito for managing encryption keys and access to the data.

Q16. You are tasked with optimizing a data transformation script that processes data from various sources. The script currently uses a straightforward linear algorithm, which has become a bottleneck due to the increasing volume of data. What programming concept can you apply to optimize the code and reduce runtime?

Select 1 option(s):

Use a single-threaded approach

Implement multi-threading or parallel processing

Increase the size of input data

Add more data validation checks

Q17. A data engineering team is operating a data pipeline on AWS. They need to set up a system to receive immediate notifications if any component of the pipeline fails or experiences issues. Which AWS service combination is most appropriate for setting up these operational alerts?

Select 1 option(s):

Use AWS Config to monitor the pipeline and send alerts via Amazon SNS.

Configure Amazon CloudWatch Alarms and integrate with Amazon SNS for notification delivery.

Implement AWS CloudTrail for logging pipeline events and Amazon SES for sending email notifications.

Set up Amazon Inspector to assess the pipeline‘s health and notify via AWS Lambda.

Q18. A financial services company is preparing for a regulatory audit and needs to provide detailed logs of all data processing activities within their AWS environment. Which AWS service should they use to extract these logs for the audit?

Select 1 option(s):

Use AWS CloudTrail to extract logs of all data processing activities.

Implement Amazon CloudWatch to generate detailed operational logs.

Configure Amazon Inspector to provide security assessment logs.

Utilize AWS Config to extract configuration change logs.

Q19. A company wants to ensure that all data in their Amazon S3 bucket is automatically deleted when it reaches 180 days of age. What AWS service or feature should they use to achieve this?

Select 1 option(s):

Amazon S3 Object Lock

Amazon S3 Versioning

Amazon S3 Glacier

Amazon S3 Lifecycle policies

Q20. A multinational corporation needs to ensure that an AWS KMS key used for encrypting data in its primary AWS account is also accessible by its subsidiarys AWS account for decryption purposes. What method should they use to achieve this?

Select 1 option(s):

Configure Amazon S3 cross-region replication to replicate the encrypted data along with the KMS key.

Modify the KMS key policy to allow the subsidiary‘s AWS account to use the key for decryption.

Create a new KMS key in the subsidiary‘s AWS account and share it with the primary account.

Use AWS DataSync to synchronize the KMS key between the two AWS accounts.

Q21. A data analyst needs to move large datasets from Amazon S3 to Amazon Redshift for analysis. Which AWS service should the analyst use to efficiently perform this data transfer while optimizing costs?

Select 1 option(s):

Use AWS Data Pipeline to create a data transfer pipeline.

Use AWS Lambda functions to copy data from S3 to Redshift.

Use Amazon Redshift Spectrum to directly query S3 data.

Use the AWS Snowball service to physically transfer data.

Q22. The operations team of a large enterprise needs to set up a robust logging mechanism for their multi-tier web application hosted on AWS. The goal is to enable real-time monitoring and timely alerting for operational issues. What is the most effective AWS solution to meet these requirements?

Select 1 option(s):

Deploy AWS Config for detailed logging and real-time monitoring of the web application.

Utilize Amazon CloudWatch Logs and Alarms for real-time log monitoring and alerting.

Implement AWS CloudTrail for logging all user activities and API calls related to the web application.

Use Amazon Inspector for continuous assessment and logging of the application‘s security posture.

Q23. An organization needs to ensure compliance with regulatory standards by keeping a record of every API call made to its AWS services, including who made the call, from where, and when. What AWS service should the organization use to meet these compliance requirements?

Select 1 option(s):

Configure Amazon S3 access logs to record all API activities.

Implement Amazon Macie to monitor and log data access and usage.

Use AWS CloudTrail to log every API call made to AWS services.

Enable Amazon GuardDuty for continuous monitoring and logging.

Q24. A data analytics team is using Amazon Redshift for their data warehousing needs. They need to ensure that all data in transit and at rest is encrypted. They also require centralized management of the encryption keys. What approach should they take?

Select 1 option(s):

Enable Amazon Redshift‘s automatic encryption feature using AWS KMS.

Configure Network Access Control Lists (NACLs) to encrypt data in transit and at rest.

Use Amazon Redshift‘s built-in encryption mechanism with Amazon-managed keys.

Encrypt the data manually before loading it into Amazon Redshift.

Q25. A data engineer needs to set up a mechanism to track and log all API calls made to the Amazon S3 service, including access requests and changes made to S3 buckets and objects. What AWS service should be utilized for this purpose?

Select 1 option(s):

Enable logging in each Amazon S3 bucket to track access and changes.

Configure AWS CloudTrail to log S3 API calls and access requests.

Use Amazon CloudWatch Events to monitor and log S3 API activities.

Implement AWS Lambda functions to record and store logs for S3 API calls.

Q26. A company wants to ensure compliance and security by monitoring and logging every access to their AWS services. Which AWS service should they primarily use to achieve comprehensive access logging?

Select 1 option(s):

A company wants to ensure compliance and security by monitoring

Use Amazon Simple Notification Service (SNS) for real-time access notifications.

Implement AWS CloudTrail to log and monitor actions taken on AWS services.

Configure AWS Config to record and assess configurations of AWS resources.

Q27. A company has large datasets used for monthly business analytics. These datasets are frequently accessed for a week after their generation but are rarely accessed thereafter. The company wants to optimize storage costs based on this data access pattern. Which storage strategy should they implement?

Select 1 option(s):

Store all data in Amazon S3 Standard and regularly move to Amazon S3 Glacier.

Use Amazon S3 Intelligent-Tiering for automatic cost optimization based on access patterns.

Keep all data in Amazon RDS to facilitate regular access.

Archive all data immediately to Amazon S3 Glacier.

Q28. The IT department of a company needs to review and analyze access patterns and modifications to their Amazon S3 buckets over the past year for a compliance audit. What method should they use to gather this information?

Select 1 option(s):

Enable and review Amazon S3 server access logging for historical access patterns and modifications.

Extract this information from AWS CloudTrail logs for the specified period.

Use Amazon CloudWatch metrics to review historical access and modifications.

Configure AWS Config to retrospectively track and report access and modifications to S3 buckets.

Q29. A company is using AWS Lambda to process data, and they need to ensure that each Lambda function has only the permissions necessary for its specific operation, which are not covered by existing AWS managed policies. How should they proceed?

Select 1 option(s):

Attach the AWSLambdaFullAccess managed policy to each Lambda function for simplicity.

Create custom IAM roles with minimal necessary permissions for each Lambda function.

Implement a single IAM user with administrative privileges and use its credentials in all Lambda functions.

Utilize Amazon Cognito identity pools to assign permissions to Lambda functions.

Q30. An online media streaming service needs to efficiently manage their media content, which includes a frequently accessed current library (hot data) and an extensive archive of old movies and shows (cold data). The solution should optimize for access speed for current content and cost for archived content. What AWS storage solutions should they implement?

Select 1 option(s):

Hot Data: Amazon S3, Cold Data: Amazon S3 Glacier

Hot Data: Amazon EBS, Cold Data: Amazon RDS

Hot Data: Amazon EC2 Instance Storage, Cold Data: Amazon EFS

Hot Data: Amazon DynamoDB, Cold Data: AWS Snowball

Q31. The operations team of a company wants to ensure the high availability and performance of their Amazon Redshift data warehouse. They need a solution to continuously monitor the database and send notifications if certain performance metrics degrade. What AWS service should they primarily utilize for this requirement?

Select 1 option(s):

Configure AWS CloudTrail to monitor Redshift and send notifications.

Use Amazon CloudWatch to track Redshift performance metrics and set up alarms.

Implement Amazon Inspector to assess and monitor the Redshift cluster.

Set up Amazon S3 access logs for monitoring Redshift access and performance.

Q32. A media company has a requirement to process log files stored in Amazon S3 every Monday and Thursday. Which service should they use to schedule and automate this data processing task?

Select 1 option(s):

AWS Lambda

AWS Data Pipeline

Amazon EC2

Amazon EMR

Q33. A data analyst needs to calculate a 7-day rolling average of sales figures stored in an Amazon Redshift data warehouse. The requirement is to include the current day and the previous six days in the average. Which SQL query correctly achieves this calculation in Amazon Redshift?

Select 1 option(s):

SELECT AVG(sales) OVER (ORDER BY date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) FROM sales_data;

SELECT date, AVG(sales) OVER (PARTITION BY date ORDER BY date ROWS 6 PRECEDING) FROM sales_data;

SELECT date, AVG(sales) FROM sales_data GROUP BY date ORDER BY date DESC LIMIT 7;

SELECT date, SUM(sales) / 7 FROM sales_data WHERE date >= CURRENT_DATE INTERVAL ‘6 days‘;

Q34. A company is using AWS Athena to analyze customer feedback stored in Amazon S3. The data includes customer ratings (1 to 5) for various services. The company wants to create a pivot-like report showing the count of each rating for each service. Assuming the table feedback has columns service and rating, which SQL query in Athena would be most appropriate?

Select 1 option(s):

SELECT service, COUNT(CASE WHEN rating = 1 THEN 1 ELSE NULL END) AS “Rating 1“, COUNT(CASE WHEN rating = 2 THEN 1 ELSE NULL END) AS “Rating 2“, FROM feedback GROUP BY service;

SELECT service, PIVOT(COUNT(rating) FOR rating IN (1, 2, 3, 4, 5)) FROM feedback GROUP BY service;

Q35. A data analyst needs to connect Amazon QuickSight to a data source for creating visualizations. The data is stored in AWS RDS with PostgreSQL. What is the first step the analyst should take in QuickSight to begin visualizing this data?

Select 1 option(s):

Set up an AWS Glue DataBrew job to prepare the data.

Create a new analysis and directly select the RDS PostgreSQL instance.

Choose “Manage data“ and create a new dataset from the RDS PostgreSQL instance.

Export data from RDS to S3 and then connect QuickSight to the S3 bucket.

Q36. An e-commerce company wants to improve the performance of its complex analytical queries on sales data, which are frequently run with only minor changes in parameters. The queries are currently impacting the performance of their transactional systems. What feature should they implement in Amazon Redshift to optimize these repeated queries?

Select 1 option(s):

Amazon Redshift Spectrum

Amazon Redshift Concurrency Scaling

Amazon Redshift Materialized Views

Amazon Redshift Data Sharing

Q37. An analytics team needs to perform complex SQL queries on a large dataset stored in Amazon S3 and join this data with tables in their Amazon Redshift data warehouse. The solution must allow for querying the S3 data without loading it into Redshift. Which AWS service is most appropriate for this requirement?

Select 1 option(s):

Amazon RDS

Amazon Redshift Spectrum

Amazon DynamoDB

AWS Lambda

Q38. An organization is utilizing AWS Lambda functions to process data stored in Amazon S3. They want to restrict each Lambda function to access only specific S3 buckets. What is the most effective way to apply this restriction?

Select 1 option(s):

Configure an IAM policy for each Lambda function, specifying access to particular S3 buckets.

Use S3 bucket policies to grant access exclusively to specific Lambda functions.

Apply Network Access Control Lists (NACLs) to restrict Lambda functions to certain S3 buckets.

Set up Amazon Cognito identity pools to manage Lambda function access to S3 buckets.

Q39. A company is using AWS CloudFormation to automate the deployment of their AWS environment. They want to ensure that the actions performed by CloudFormation are done under specific permissions without utilizing the permissions of the user executing the template. What should they implement?

Select 1 option(s):

Configure the AWS CLI with a profile having the required permissions for CloudFormation.

Create an IAM role with appropriate permissions and use service role in CloudFormation.

Set up an Amazon Cognito identity pool to manage permissions for CloudFormation deployments.

Attach the necessary permissions directly to the CloudFormation template.

Q40. A data analyst team requires read-only access to specific Amazon S3 buckets in their companys AWS environment. The security team wants to ensure this access is policy-based and adheres to best practices. How should they implement this authorization?

Select 1 option(s):

Attach an IAM managed policy with read-only access to the S3 buckets to each data analyst‘s IAM user.

Set up Amazon S3 bucket policies granting read-only access to the data analyst team‘s IP addresses.

Create a custom IAM policy with read-only access to the specified S3 buckets and associate it with the data analyst team‘s IAM role.

Implement AWS Access Keys for each data analyst that provide read-only access to the S3 buckets.

Q41. A healthcare company is using AWS for data processing and storage. They need to ensure that only the compliance team has the authorization to access patient data stored in Amazon S3 for audit purposes. Which authorization method should they use?

Select 1 option(s):

Configure Amazon S3 bucket policies to allow access only to IAM users in the compliance team.

Set up IAM roles with necessary permissions and assign these roles to the compliance team members.

Implement Network Access Control Lists (NACLs) to restrict access to the S3 buckets containing patient data.

Use AWS Key Management Service (KMS) to manage encryption keys and grant access only to the compliance team.

Q42. A data engineer is tasked with setting up an AWS Lambda function to process data from a specific DynamoDB table. According to the principle of least privilege, what is the best approach for configuring the Lambda functions IAM role?

Select 1 option(s):

Assign an IAM role to the Lambda function with full access to all DynamoDB tables.

Create a custom IAM role for the Lambda function with permissions limited to only the necessary DynamoDB table.

Utilize an existing IAM role with broad database access, including RDS and Redshift, along with DynamoDB.

Implement the Lambda function without an IAM role and rely on network controls for security.

Q43. A data analytics team is working with large datasets stored in Hadoop Distributed File System (HDFS) and needs a mechanism to manage and access this data efficiently for their Spark and Hadoop jobs. They require a system to store and retrieve metadata and structure information. Which tool should they use to build and reference a data catalog for these requirements?

Select 1 option(s):

AWS Glue Data Catalog

Apache Hive Metastore

Amazon Redshift

Amazon DynamoDB

Q44. A team needs to create an interactive dashboard for their sales data stored in Amazon S3. They want to use an AWS service that allows them to build visualizations, perform ad-hoc analysis, and generate insights from the data. Which AWS service would best meet these requirements?

Select 1 option(s):

Amazon QuickSight

AWS Glue DataBrew

Amazon Redshift

AWS Lambda

Q45. An organization using a big data environment wants to manage the schema and metadata of their data stored across different systems including HDFS and Amazon S3. They need a centralized service to define and maintain the structure of their data for querying and analysis. Which solution should they implement?

Select 1 option(s):

Apache Hive Metastore

AWS DataSync

Amazon RDS

AWS Glue Data Catalog

Q46. A financial institution is using AWS and needs to ensure that only the finance department has access to certain confidential financial reports stored in S3 buckets. They have tagged these S3 buckets with Department: Finance. What is the most effective way to restrict access to these buckets based on the tags?

Select 1 option(s):

Implement AWS IAM roles with policies that allow access only to resources tagged with “Department: Finance.“

Configure S3 bucket policies to grant access exclusively to users with finance-related IAM credentials.

Set up AWS Resource Access Manager (RAM) to share resources based on the “Department: Finance“ tag.

Use AWS Security Groups to restrict access to the S3 buckets based on the department tag.

Q47. A financial institution uses Amazon Redshift for data analysis and AWS Lake Formation for data governance. They require strict control over who can access sensitive financial records. What is the best practice for managing access to this sensitive data using Lake Formation?

Select 1 option(s):

Implement Amazon Redshift database views to restrict access to sensitive data.

Use Lake Formation to set fine-grained access controls on sensitive data for specific users or roles.

Store sensitive data in a separate Amazon S3 bucket and restrict access using S3 bucket policies.

Configure AWS Secrets Manager to control user access to sensitive financial records in Amazon Redshift.

Q48. An enterprises data lake on Amazon S3 is partitioned by both time and product categories. They frequently add new data to these partitions. To enable efficient querying with Amazon Athena, what should they implement to ensure the Athena data catalog reflects the latest partitions?

Select 1 option(s):

Regularly schedule Amazon Athena to update its data catalog.

Utilize Amazon Redshift to manage the data catalog.

Employ AWS Glue Crawlers to dynamically update the data catalog.

Manually execute ALTER TABLE commands in Athena for new partitions.

Q49. A company is developing a web application that connects to an Amazon RDS database. They want to securely store and manage the database credentials. Which service should they use to achieve this in compliance with AWS best practices for credential storage?

Select 1 option(s):

Store the credentials in an Amazon S3 bucket with server-side encryption.

Use AWS Secrets Manager to securely store and automatically rotate the database credentials.

Keep the credentials hardcoded within the application‘s source code for direct access.

Implement AWS IAM database authentication for the RDS database.

Q50. A data engineering team is developing a data pipeline on AWS and needs to implement logging for their application. They want to ensure that logs are easily accessible and can be analyzed for troubleshooting. Which AWS service should they primarily use for application logging?

Select 1 option(s):

Use Amazon Kinesis Data Firehose to stream logs to an Amazon S3 bucket.

Implement Amazon CloudWatch Logs for logging and monitoring application data.

Store logs in an Amazon DynamoDB table for easy retrieval and analysis.

Configure AWS Step Functions to log application data and monitor the pipeline.

Q51. An AWS-based application generates a large volume of log data. The data engineering team needs to aggregate, store, and analyze these logs efficiently. What is the most effective AWS solution for handling these large-scale application logs?

Select 1 option(s):

Directly store the logs in an Amazon Redshift cluster for real-time analysis.

Utilize Amazon CloudWatch Logs for aggregation and storage, and then analyze the data using Amazon Athena.

Save log data to Amazon S3 and use AWS Glue for ETL processing.

Configure Amazon QuickSight to directly collect and analyze the log data.

Q52. A company has a large dataset stored in Amazon S3, and they want to implement a cost-effective solution to automatically transition objects to a lower-cost storage class after a certain period of inactivity. What AWS service or feature should they use to achieve this?

Select 1 option(s):

Amazon S3 Versioning

Amazon S3 Object Lock

Amazon S3 Lifecycle policies

Amazon S3 Access Points

Q53. An e-commerce company wants to catalog customer transaction data stored in Amazon DynamoDB and product information stored in Amazon Redshift. They need a service to connect to these data stores and facilitate cataloging. Which AWS service should they use to create these connections?

Select 1 option(s):

Amazon EC2

AWS Lambda

AWS Glue

Amazon EMR

Q54. A company is using Amazon RDS for their customer database. They need to ensure that sensitive customer data is not visible in plain text when accessed by certain applications. Which approach should they take to protect this sensitive data?

Select 1 option(s):

Use Amazon RDS encryption at rest feature to encrypt the entire database.

Implement data masking in the application layer to obscure sensitive customer data.

Configure Network Access Control Lists (NACLs) to prevent unauthorized access to the data.

Store the sensitive data in a separate Amazon S3 bucket with server-side encryption.

Q55. A media company needs to retain its video content for compliance reasons and may need to access it infrequently for analysis. Which AWS service or feature can best fulfill this requirement while minimizing costs?

Select 1 option(s):

Store the video content in Amazon S3 with versioning enabled.

Use Amazon EBS volumes for each video and store them in an S3 bucket.

Store the video content in Amazon S3 Glacier.

Configure an Amazon RDS database to store the video metadata.

Q56. A company is using AWS Lake Formation alongside Amazon Redshift for their data warehousing and analytics. They want to manage permissions for different analyst teams, ensuring specific teams can only query data relevant to their projects. How should they implement this using Lake Formation?

Select 1 option(s):

Configure Network Access Control Lists (NACLs) in Amazon Redshift to control data access for different teams.

Utilize AWS IAM roles and policies to grant the analyst teams access to specific datasets in Lake Formation.

Grant permissions directly in Amazon Redshift for each team to access only their relevant datasets.

Use Lake Formation‘s permissions model to define and grant data access permissions to the different analyst teams.

Q57. You are developing a data ingestion and transformation pipeline for processing large volumes of log data. The pipeline is currently taking longer than expected to process the data, impacting the real-time nature of the application. After analyzing the code, you identify a section that iterates over the entire dataset multiple times unnecessarily. What is the most effective way to optimize the code and reduce runtime?

Select 1 option(s):

Increase the number of iterations

Implement caching for intermediate results

Introduce additional sleep intervals in the code

Decrease the batch size of data processed

Q58. A data analytics team is using Amazon Athena for querying data stored in an S3 data lake. The organization has implemented AWS Lake Formation for enhanced data governance. The team requires specific users to have access only to certain datasets within the data lake. How should they configure access in Athena using Lake Formation?

Select 1 option(s):

Set up IAM policies to grant specific users access to the relevant S3 buckets where the datasets are stored.

Utilize AWS Lake Formation to grant fine-grained access permissions to specific datasets for the users in Athena.

Implement Amazon Cognito user pools to control access permissions to the datasets in Athena.

Configure Amazon S3 bucket policies to restrict user access to the datasets needed for querying in Athena.

Q59. A data engineer needs to ensure that specific data files in an Amazon S3 bucket are automatically deleted when they reach 90 days of age, while other files should remain in the bucket indefinitely. What is the most efficient way to accomplish this?

Select 1 option(s):

Create an S3 bucket policy to delete all files older than 90 days and apply it to the entire bucket.

Use Amazon S3 Object Lock to set a retention period of 90 days for the specific files to be deleted.

Configure an S3 lifecycle policy to delete files older than 90 days and apply it to the entire bucket.

Use Amazon S3 versioning to delete specific file versions that are older than 90 days.

Q60. A financial analytics firm requires a storage solution for processing real-time market data. This data is accessed frequently and needs to be available with high throughput and low latency. Simultaneously, they need to store historical market data, which is accessed infrequently but needs to be retained for regulatory compliance. Which combination of AWS storage solutions best meets these hot and cold data requirements?

Select 1 option(s):

Hot Data: Amazon S3, Cold Data: Amazon Glacier

Hot Data: Amazon EBS, Cold Data: Amazon S3

Hot Data: Amazon RDS, Cold Data: Amazon Glacier

Hot Data: Amazon EC2 Instance Storage, Cold Data: Amazon S3 Glacier

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AWS Data Engineer Associate - Test 15

Q1. An AWS data pipeline using Amazon Redshift is experiencing slower query response times than usual. What is the first action the data engineer should take to identify the cause of the slowdown?

Q3. A company is looking for a solution to efficiently unload data from Amazon Redshift to Amazon S3 in a structured format for long-term storage and analysis. Which method should the company use to achieve this?

Q4. A data analyst is using Amazon Athena to analyze web traffic data stored in Amazon S3. The requirement is to create a persistent summary view that aggregates daily traffic data by region. Which approach should the analyst use in Athena to achieve this?

Q5. An online media company stores a vast amount of video content. New content is accessed frequently, but older content is only occasionally accessed. The company seeks a cost-effective storage solution that aligns with this lifecycle. What storage strategy should they adopt?

Q8. A data engineer is optimizing an Amazon Redshift data warehouse to improve query performance. The data warehouse contains large tables with historical data. Which of the following practices should the engineer implement to enhance query performance?

Q9. A company is using Amazon S3 to store important data, and they want to ensure that they can recover previous versions of objects if needed. Which AWS service or feature should they enable for this purpose?

Q10. A financial institution is required to retain customer transaction records for seven years and make them available for auditing during this period. What is the most suitable AWS service or feature for managing these records?

Q11. A company hosts a critical database on Amazon RDS for MySQL to support its e-commerce platform. To ensure data resiliency and availability, which AWS service or feature should the company implement?

Q12. You are working on a data processing application that needs to efficiently search for specific items in a large dataset. The dataset is organized as a hierarchical structure with parent and child nodes. Which data structure is best suited for this scenario?

Q15. A company is storing sensitive financial data in Amazon S3 and requires that the data is encrypted at rest. They want to ensure that they maintain control over the encryption keys used. Which AWS service should they use for managing these encryption keys?

Q17. A data engineering team is operating a data pipeline on AWS. They need to set up a system to receive immediate notifications if any component of the pipeline fails or experiences issues. Which AWS service combination is most appropriate for setting up these operational alerts?

Q18. A financial services company is preparing for a regulatory audit and needs to provide detailed logs of all data processing activities within their AWS environment. Which AWS service should they use to extract these logs for the audit?

Q19. A company wants to ensure that all data in their Amazon S3 bucket is automatically deleted when it reaches 180 days of age. What AWS service or feature should they use to achieve this?

Q20. A multinational corporation needs to ensure that an AWS KMS key used for encrypting data in its primary AWS account is also accessible by its subsidiarys AWS account for decryption purposes. What method should they use to achieve this?

Q21. A data analyst needs to move large datasets from Amazon S3 to Amazon Redshift for analysis. Which AWS service should the analyst use to efficiently perform this data transfer while optimizing costs?

Q22. The operations team of a large enterprise needs to set up a robust logging mechanism for their multi-tier web application hosted on AWS. The goal is to enable real-time monitoring and timely alerting for operational issues. What is the most effective AWS solution to meet these requirements?

Q23. An organization needs to ensure compliance with regulatory standards by keeping a record of every API call made to its AWS services, including who made the call, from where, and when. What AWS service should the organization use to meet these compliance requirements?

Q24. A data analytics team is using Amazon Redshift for their data warehousing needs. They need to ensure that all data in transit and at rest is encrypted. They also require centralized management of the encryption keys. What approach should they take?

Q25. A data engineer needs to set up a mechanism to track and log all API calls made to the Amazon S3 service, including access requests and changes made to S3 buckets and objects. What AWS service should be utilized for this purpose?

Q26. A company wants to ensure compliance and security by monitoring and logging every access to their AWS services. Which AWS service should they primarily use to achieve comprehensive access logging?

Q28. The IT department of a company needs to review and analyze access patterns and modifications to their Amazon S3 buckets over the past year for a compliance audit. What method should they use to gather this information?

Q29. A company is using AWS Lambda to process data, and they need to ensure that each Lambda function has only the permissions necessary for its specific operation, which are not covered by existing AWS managed policies. How should they proceed?

Q32. A media company has a requirement to process log files stored in Amazon S3 every Monday and Thursday. Which service should they use to schedule and automate this data processing task?

Q33. A data analyst needs to calculate a 7-day rolling average of sales figures stored in an Amazon Redshift data warehouse. The requirement is to include the current day and the previous six days in the average. Which SQL query correctly achieves this calculation in Amazon Redshift?

Q35. A data analyst needs to connect Amazon QuickSight to a data source for creating visualizations. The data is stored in AWS RDS with PostgreSQL. What is the first step the analyst should take in QuickSight to begin visualizing this data?

Q38. An organization is utilizing AWS Lambda functions to process data stored in Amazon S3. They want to restrict each Lambda function to access only specific S3 buckets. What is the most effective way to apply this restriction?

Q39. A company is using AWS CloudFormation to automate the deployment of their AWS environment. They want to ensure that the actions performed by CloudFormation are done under specific permissions without utilizing the permissions of the user executing the template. What should they implement?

Q40. A data analyst team requires read-only access to specific Amazon S3 buckets in their companys AWS environment. The security team wants to ensure this access is policy-based and adheres to best practices. How should they implement this authorization?

Q41. A healthcare company is using AWS for data processing and storage. They need to ensure that only the compliance team has the authorization to access patient data stored in Amazon S3 for audit purposes. Which authorization method should they use?

Q42. A data engineer is tasked with setting up an AWS Lambda function to process data from a specific DynamoDB table. According to the principle of least privilege, what is the best approach for configuring the Lambda functions IAM role?

Q44. A team needs to create an interactive dashboard for their sales data stored in Amazon S3. They want to use an AWS service that allows them to build visualizations, perform ad-hoc analysis, and generate insights from the data. Which AWS service would best meet these requirements?

Q47. A financial institution uses Amazon Redshift for data analysis and AWS Lake Formation for data governance. They require strict control over who can access sensitive financial records. What is the best practice for managing access to this sensitive data using Lake Formation?

Q48. An enterprises data lake on Amazon S3 is partitioned by both time and product categories. They frequently add new data to these partitions. To enable efficient querying with Amazon Athena, what should they implement to ensure the Athena data catalog reflects the latest partitions?

Q49. A company is developing a web application that connects to an Amazon RDS database. They want to securely store and manage the database credentials. Which service should they use to achieve this in compliance with AWS best practices for credential storage?

Q50. A data engineering team is developing a data pipeline on AWS and needs to implement logging for their application. They want to ensure that logs are easily accessible and can be analyzed for troubleshooting. Which AWS service should they primarily use for application logging?

Q51. An AWS-based application generates a large volume of log data. The data engineering team needs to aggregate, store, and analyze these logs efficiently. What is the most effective AWS solution for handling these large-scale application logs?

Q52. A company has a large dataset stored in Amazon S3, and they want to implement a cost-effective solution to automatically transition objects to a lower-cost storage class after a certain period of inactivity. What AWS service or feature should they use to achieve this?

Q53. An e-commerce company wants to catalog customer transaction data stored in Amazon DynamoDB and product information stored in Amazon Redshift. They need a service to connect to these data stores and facilitate cataloging. Which AWS service should they use to create these connections?

Q54. A company is using Amazon RDS for their customer database. They need to ensure that sensitive customer data is not visible in plain text when accessed by certain applications. Which approach should they take to protect this sensitive data?

Q55. A media company needs to retain its video content for compliance reasons and may need to access it infrequently for analysis. Which AWS service or feature can best fulfill this requirement while minimizing costs?

Q56. A company is using AWS Lake Formation alongside Amazon Redshift for their data warehousing and analytics. They want to manage permissions for different analyst teams, ensuring specific teams can only query data relevant to their projects. How should they implement this using Lake Formation?

Q59. A data engineer needs to ensure that specific data files in an Amazon S3 bucket are automatically deleted when they reach 90 days of age, while other files should remain in the bucket indefinitely. What is the most efficient way to accomplish this?

Q20. A multinational corporation needs to ensure that an AWS KMS key used for encrypting data in its primary AWS account is also accessible by its subsidiarys AWS account for decryption purposes. What method should they use to achieve this?

Q40. A data analyst team requires read-only access to specific Amazon S3 buckets in their companys AWS environment. The security team wants to ensure this access is policy-based and adheres to best practices. How should they implement this authorization?

Q42. A data engineer is tasked with setting up an AWS Lambda function to process data from a specific DynamoDB table. According to the principle of least privilege, what is the best approach for configuring the Lambda functions IAM role?

Q48. An enterprises data lake on Amazon S3 is partitioned by both time and product categories. They frequently add new data to these partitions. To enable efficient querying with Amazon Athena, what should they implement to ensure the Athena data catalog reflects the latest partitions?