Free AWS Certified Data Engineer (DEA-C01) Practice Test 12

Free AWS Certified Data Engineer Associate Exam (DEA-C01) Practice Test 12 is for people who finished a course and still are not getting callbacks. Completion badges are easy to collect. A proctored DEA-C01 is not. AWS is the most popular cloud platform used by companies worldwide, so hiring teams already know this exam. Certification benefits include third-party scoring, a credential recruiters can filter on, and a better shot at job offers in AWS and data engineering than another login certificate.

Salary talk should match the level you can defend in an interview. Junior data engineers often average about $72,000, with stronger starts near $105,000. Mid-level data engineers often earn $119,000 to $156,000. Senior data engineers often earn about $147,000 to $181,000 or above. Employers that hire this profile include Nike, Target, and Costco.

SynergisticIT JOPP helps jobseekers get certified, prepared, and hired at top tech companies through our Job Placement programs — Java DevOps Full Stack JOPP and Data Science JOPP.

If you want to learn how to get hired as a Data Engineer, Data Scientist, Data Analyst, AI or ML engineer, or a software engineer, contact SynergisticIT for expert upskilling and marketing connections to companies. Visit Contact Us and SynergisticIT JOPP.

Welcome to your AWS Data Engineer Associate – Test-12

Name

Phone

Q1. A data engineering team needs to aggregate large volumes of web traffic data stored in Amazon S3 and generate summarized reports on a daily basis. The solution should optimize for query performance and cost. Which AWS service or combination of services is most suitable for this task?

Select 1 option(s):

Use Amazon Athena to directly query and aggregate data in Amazon S3.

Implement an AWS Glue ETL job to transform and aggregate the data, then query using Amazon Redshift.

Store the data in Amazon DynamoDB and use DynamoDB Streams for aggregation.

Process the data using AWS Lambda and store aggregated results in Amazon RDS for querying.

Q2. In an effort to enhance data quality, a team is using AWS Glue DataBrew to clean a large dataset. They need to standardize the formatting of date fields which are currently in various formats. What is the most effective method to accomplish this in AWS Glue DataBrew?

Select 1 option(s):

Utilize the “Standardize dates“ transformation to convert date fields into a uniform format.

Export the dataset to Amazon S3, and then use an AWS Lambda function to standardize the date formats.

Manually adjust the date formats in each row using the DataBrew spreadsheet editor.

Implement an AWS Step Functions workflow to orchestrate multiple DataBrew jobs, each designed for a specific date format.

Q3. A data engineering team needs to ensure secure access to an Amazon Redshift data warehouse. They want to restrict access to specific IP addresses from their corporate network. Which AWS feature should they use to configure this access control?

Select 1 option(s):

Amazon Redshift Spectrum

AWS Identity and Access Management (IAM) Policies

Amazon Redshift Security Groups

AWS Lambda function triggers

Q4. A company is setting up a data analysis environment on AWS. The data engineers require access to Amazon S3, Amazon Redshift, and AWS Glue. To manage permissions efficiently, what is the best approach for granting them the necessary access?

Select 1 option(s):

Create individual IAM users for each data engineer and attach policies for S3, Redshift, and Glue directly to each user.

Establish an IAM group for data engineers, and attach policies for S3, Redshift, and Glue to this group.

Use AWS Organizations to create a separate account for data engineers and provide blanket permissions for S3, Redshift, and Glue.

Configure a Network Access Control List (NACL) allowing data engineers access to S3, Redshift, and Glue.

Q5. A data engineering team is building an application that requires connecting to a MySQL database and a Microsoft SQL Server database. Which connectivity method should they use to enable their application to interact with these different database systems?

Select 1 option(s):

Java Database Connectivity (JDBC)

Open Database Connectivity (ODBC)

Direct API calls to the databases

Amazon RDS Data API

Q6. A retail company needs to integrate sales data from its online store, hosted on Amazon RDS, with inventory data from a third-party system, accessible via an API. The integrated data will then be used for analytics. Which AWS service is most suitable for integrating these disparate data sources?

Select 1 option(s):

Amazon Redshift

AWS Lambda

AWS Glue

Amazon Kinesis

Q7. A company has multiple applications that produce data, and they want to centralize the data from these applications into a common data store on AWS. They also want to ensure that the data is regularly updated in the data store. Which AWS service is suitable for this data consolidation and maintenance task?

Select 1 option(s):

Amazon S3

Amazon RDS

Amazon Redshift

AWS DataSync

Q8. An enterprise plans to deploy a customer relationship management (CRM) system that requires a relational database with high availability, multi-region read replicas, and the ability to scale computing and storage resources independently. Which AWS service best fits these requirements?

Select 1 option(s):

Amazon RDS

Amazon DynamoDB

Amazon Redshift

Amazon Aurora

Q9. A data engineer is required to create an SQL query to list all products, their prices, and the names of the categories they belong to. The relevant tables are Products and Categories, linked by the CategoryID field. Which query would correctly accomplish this task?

Select 1 option(s):

Q10. During the execution of an AWS Glue ETL job, a data engineer notices that the job is taking significantly longer than expected to complete. What should be the first step in troubleshooting this performance issue?

Select 1 option(s):

Increase the number of DPUs (Data Processing Units) allocated to the job.

Check the job logs in Amazon CloudWatch for any error messages or warnings.

Immediately switch to a different ETL tool.

Reduce the data sample size in the ETL job script.

Q11. A company is performing complex data transformations and analytics on a large dataset using Apache Spark. They need to ensure high availability and fault tolerance for their Spark application. What feature of Apache Spark should they primarily leverage to achieve this?

Select 1 option(s):

A company is performing complex data transformations and analytics on a

Spark SQL for structured data processing

Spark‘s Resilient Distributed Dataset (RDD) feature

Integration of Spark with Amazon Kinesis

Q12. A company is developing a new web application that requires a relational database with the ability to handle complex queries and joins. The database should also be cost-effective and offer features like automated backups and easy scaling. Which AWS service meets these requirements?

Select 1 option(s):

Amazon RDS

Amazon DynamoDB

Amazon EC2 with self-managed database

Amazon Redshift

Q13. A marketing analytics company needs to store and analyze large volumes of customer data from various sources. The solution requires fast query performance for complex analytical queries and efficient storage for historical data. Which AWS service best fits these access patterns and requirements?

Select 1 option(s):

Amazon DynamoDB

Amazon Redshift

Amazon S3

Amazon RDS

Q14. An organization requires a solution to analyze streaming data in real-time from multiple sources. The solution must be able to handle large-scale data processing and provide the flexibility to use various big data frameworks. Which AWS service is most appropriate for this scenario?

Select 1 option(s):

Amazon Kinesis

Amazon S3

Amazon Redshift

Amazon EMR

Q15. A data engineering team is tasked with integrating external data sources into their data lake on AWS. They want to consume data from external APIs and ensure that the data is regularly updated in their data lake. Which AWS service should the team use to achieve this?

Select 1 option(s):

Amazon S3

AWS Lambda

AWS Glue

Amazon API Gateway

Q16. A team is deploying AWS infrastructure using AWS CloudFormation. They need to ensure that CloudFormation has the necessary permissions to create, update, and delete resources as specified in the templates. Which approach should they take to provide these permissions?

Select 1 option(s):

Attach an IAM user policy with the required permissions directly to the CloudFormation service.

Create an IAM role with the necessary permissions and associate it with the CloudFormation stack.

Use the root account credentials in CloudFormation templates for unrestricted access to AWS resources.

Configure Network Access Control Lists (NACLs) to grant CloudFormation the necessary permissions.

Q17. A large retail company is streaming high-volume sales data from multiple stores into a single Amazon Kinesis Data Stream. They want to distribute this data to multiple downstream processing systems for real-time analytics. Which AWS service should be used to efficiently manage the fan-out of this streaming data?

Select 1 option(s):

Amazon S3

AWS Lambda

Amazon Kinesis Data Firehose

Amazon Kinesis Data Analytics

Q18. An e-commerce company wants to build a system for processing user activity and clickstream data in real-time to provide personalized shopping experiences. The system must be able to handle large-scale and high-velocity data streams. Which AWS service is most suitable for this use case?

Select 1 option(s):

Amazon MSK (Managed Streaming for Kafka)

Amazon Redshift

Amazon EC2

Amazon Kinesis Data Streams

Q19. A company needs to analyze large volumes of data from various sources and perform complex queries. The solution should be cost-effective while offering high-performance analytics. Which AWS service aligns best with these requirements?

Select 1 option(s):

Amazon RDS

Amazon DynamoDB

Amazon Redshift

Amazon S3

Q20. An e-commerce platform requires a database solution for managing its product catalog, which frequently changes and includes a variety of attributes. The solution must offer flexible schema design to accommodate the varying attributes and ensure low-latency access for a seamless user experience. Which AWS service is the best choice?

Select 1 option(s):

Amazon DynamoDB

Amazon RDS

Amazon Redshift

Amazon ElasticSearch Service

Q21. A new application deployed on AWS requires different levels of access to AWS resources for various components. What is the recommended approach to manage these access levels effectively?

Select 1 option(s):

Create a single IAM user with administrative privileges and use it across all application components.

Set up individual IAM roles for each application component with tailored permissions.

Implement one IAM group and add all application components to this group with general permissions.

Use a Network Access Control List (NACL) to manage access to AWS resources for each application component.

Q22. A data analysis team working with Amazon Redshift needs to regularly generate reports based on large and complex join operations across multiple tables. These reports are time-consuming to generate. Which Redshift feature can help speed up the generation of these reports by caching the results of these operations?

Select 1 option(s):

Amazon Redshift RA3 Nodes

Amazon Redshift Elastic Resize

Amazon Redshift Materialized Views

Amazon Redshift Snapshot Restore

Q23. A company is deploying an AWS Lambda function that needs to read data from an Amazon S3 bucket and write logs to Amazon CloudWatch. Which of the following is the most appropriate way to set up IAM roles for this Lambda function?

Select 1 option(s):

Assign an AWS managed policy with full S3 and CloudWatch access directly to the Lambda function.

Create a custom IAM role with the necessary permissions for S3 and CloudWatch and associate it with the Lambda function.

Use AWS Organizations to manage permissions for the Lambda function across different AWS accounts.

Configure Network Access Control Lists (NACLs) to allow the Lambda function access to S3 and CloudWatch.

Q24. A mobile gaming company requires a database solution to manage user data and game state information. The database must be able to handle high throughput, provide low-latency read and write operations, and scale automatically with user demand. Which AWS service is the most suitable for these requirements?

Select 1 option(s):

Amazon RDS

Amazon DynamoDB

Amazon Redshift

Amazon S3

Q25. A company is using Amazon API Gateway for its serverless application. They want to ensure that only certain AWS services, like AWS Lambda and Amazon S3, can invoke the API. What is the recommended way to configure access control for this scenario?

Select 1 option(s):

Configure network Access Control Lists (ACLs) to allow only AWS Lambda and Amazon S3 to access the API Gateway.

Set up an Amazon Cognito user pool to restrict access to the API Gateway from specified AWS services.

Create IAM roles with policies that grant access to the API Gateway and assign these roles to the allowed AWS services.

Enable API Gateway resource policies to specify allowed source ARNs from AWS Lambda and Amazon S3.

Q26. A data engineering team is evaluating the use of AWS services for a new real-time analytics application. The application will experience unpredictable, highly variable workloads. What is the most appropriate choice for data processing in this scenario, considering the tradeoffs between provisioned services and serverless services?

Select 1 option(s):

Amazon EC2 instances with Auto Scaling.

AWS Lambda for serverless data processing

Provisioned Amazon Redshift clusters.

Amazon RDS with provisioned IOPS.

Q27. A data engineering team wants to automatically trigger an AWS Lambda function for data processing every day at midnight. The process should integrate with other AWS services for additional tasks. Which AWS service should be used to schedule and trigger this daily event?

Select 1 option(s):

Amazon CloudWatch Events

AWS Step Functions

Amazon Simple Notification Service (SNS)

Amazon Elastic Container Service (ECS)

Q28. A media company is streaming a mix of structured and unstructured data, including video metadata and user interaction logs, for real-time analysis. The solution must handle large volumes of data at high velocity. Which AWS service is best suited for this scenario?

Select 1 option(s):

Amazon RDS

Amazon DynamoDB

Amazon Kinesis

AWS Lambda

Q29. An organization using AWS needs to ensure that their EC2 instances can access specific AWS services like Amazon S3 and Amazon DynamoDB without storing access keys on the instances. What is the recommended method to securely manage this access?

Select 1 option(s):

Attach IAM user policies directly to the EC2 instances for the required services.

Create IAM roles with necessary permissions and associate them with the EC2 instances.

Use Amazon Cognito to authenticate the EC2 instances with the required services.

Implement Network Access Control Lists (NACLs) to regulate traffic between the EC2 instances and the services.

Q30. A company is gathering data from sensors in its manufacturing plants, stored in Amazon S3, and needs to combine this data with operational data stored in an Amazon Aurora database for predictive maintenance analytics. Which AWS service should they use to integrate these data sources effectively?

Select 1 option(s):

AWS Data Pipeline

Amazon EC2

Amazon Athena

Amazon EMR

Q31. A data engineering team is using Amazon Redshift for their data warehousing needs. They need to ensure that a specific set of data is not modified during a critical analysis period. Which method should they use to manage locks and prevent modification of this data in Amazon Redshift?

Select 1 option(s):

Implement Amazon Redshift Spectrum.

Use Redshift‘s Serializable Isolation Level

Enable Multi-AZ deployments for Redshift.

Configure Redshift Data Encryption.

Q32. A company is developing an application that requires real-time ingestion of data from a social media platforms API. The ingested data will be used for immediate sentiment analysis. Which AWS service combination is most suitable for consuming the API and performing the analysis?

Select 1 option(s):

Amazon API Gateway and AWS Lambda

AWS Glue and Amazon Redshift

Amazon S3 and Amazon Athena

Amazon EC2 and Amazon RDS

Q33. A data engineering team needs to ensure that the data stored in HDFS on Amazon EMR is encrypted at rest. Which of the following is the most appropriate solution to meet this requirement?

Select 1 option(s):

Encrypt HDFS using Amazon S3 server-side encryption.

Utilize EMRFS consistent view for encryption at rest.

Implement HDFS transparent encryption with AWS KMS keys.

Apply encryption using VPC security group rules.

Q34. A data engineer is developing an application that needs to interact with Amazon S3 to store and retrieve data. The engineer is using Python for application development. Which AWS service should the engineer use to call SDKs and access Amazon S3 features from the Python code?

Select 1 option(s):

AWS Lambda

Amazon Redshift

AWS Glue

AWS SDK for Python (Boto3)

Q35. A data engineer is working on a project that involves collecting and processing large volumes of real-time data streams from IoT devices. They need to apply custom scripts for data processing and analysis on this streaming data. Which AWS service can accept custom scripts for real-time data processing and analysis?

Select 1 option(s):

Amazon S3

AWS Glue

Amazon Kinesis

Amazon Redshift

Q36. A company wants to automate the process of transforming and loading data from various sources into a data warehouse for analytics. The data engineer needs to choose an AWS service that can orchestrate and automate these ETL (Extract, Transform, Load) workflows. Which AWS service should the engineer use?

Select 1 option(s):

Amazon Redshift

Amazon S3

AWS Glue

Amazon Kinesis

Q37. A company needs to automate the execution of an AWS Glue ETL job to process data daily at midnight. Which AWS service should be used to schedule and trigger this ETL job?

Select 1 option(s):

Amazon CloudWatch

Amazon EventBridge

AWS Step Functions

Amazon Kinesis Data Firehose

Q38. A data engineer is setting up access to an Amazon RDS database for application users. The requirement is to use password-based authentication for these users. Which of the following approaches should the engineer take to implement this?

Select 1 option(s):

Configure AWS IAM user accounts with password policies and associate them with the RDS database.

Set up database users with password authentication within the RDS database instance.

Use Amazon Cognito with password-based authentication for database access.

Implement Network Access Control Lists (NACLs) with password policies for the RDS instance.

Q39. A company is setting up a new AWS environment for their web application. They want to ensure that the database servers are not directly accessible from the internet, but can still be accessed by the application servers within the same VPC. Which VPC security networking concept should they implement?

Select 1 option(s):

Place the database servers in a public subnet and control access using Network Access Control Lists (NACLs).

Use an Internet Gateway to restrict internet access to the database servers.

Place the database servers in a private subnet and configure the route table appropriately.

Implement a Virtual Private Gateway to isolate the database servers from the internet.

Q40. An organization is using Amazon EMR for their big data processing needs. They require that all data in transit within the EMR cluster be encrypted to comply with their strict data security policies. Which of the following methods should be used to achieve this requirement?

Select 1 option(s):

Use AWS KMS for server-side encryption of S3 buckets used by EMR.

Enable TLS for data in transit between EMR cluster nodes.

Implement client-side encryption before sending data to the EMR cluster.

Apply IAM roles with strict policies to the EMR cluster.

Q41. A financial institution is using Amazon RDS for their database needs. They need to ensure that data transferred between their application servers and the RDS database is encrypted during transit. Which option should they configure to enable encryption in transit for RDS effectively?

Select 1 option(s):

Use AWS KMS-managed keys for server-side encryption in RDS.

Implement SSL/TLS for secure connections between application servers and RDS.

Enable VPC security group rules for encrypted data transit in RDS.

Utilize AWS Secrets Manager for encrypted data transfer to RDS.

Q42. A data engineer needs to choose between AWS managed database service Amazon RDS and self-managed databases on Amazon EC2 instances. What is a primary difference regarding the authentication mechanisms between these two services?

Select 1 option(s):

Amazon RDS provides automated password rotation, which is not available with self-managed databases on EC2.

Self-managed databases on EC2 inherently support biometric authentication, unlike Amazon RDS.

Amazon RDS only allows database authentication through AWS IAM, while EC2-based databases do not support IAM.

Self-managed databases on EC2 require manual setup and maintenance of database authentication, as opposed to RDS which handles these aspects.

Q43. A financial services company is setting up a system to process high-volume, real-time stock market data for immediate analysis. Which AWS service is most suitable for reading and processing this type of streaming data?

Select 1 option(s):

Amazon DynamoDB Streams

AWS Database Migration Service (AWS DMS)

Amazon Kinesis

Amazon RDS

Q44. A company needs to ingest historical log data stored in Amazon S3 into a data warehouse for analysis. The data ingestion process is required to happen on a weekly basis. Which AWS service is most appropriate for this data ingestion pattern?

Select 1 option(s):

AWS Lambda

AWS Glue

Amazon Kinesis Data Firehose

Amazon EC2

Q45. An enterprise intends to analyze its operational data stored in Parquet format using serverless computing. The analysis requires fast query performance and the ability to handle complex queries. Which combination of AWS services should be used?

Select 1 option(s):

Amazon Redshift and AWS Lambda

Amazon S3 and Amazon Athena

Amazon EC2 and Amazon EBS

Amazon RDS and Amazon DynamoDB

Q46. A data engineer is designing a data warehouse solution for a project and needs to perform complex data transformations and analysis using custom scripts. Which AWS service is suitable for executing custom scripts and allows scripting for data processing tasks, including data transformation and analysis?

Select 1 option(s):

Amazon S3

AWS Glue

Amazon RDS (Relational Database Service)

Amazon Kinesis

Q47. Your company plans to store a large dataset of historical sales data in a data lake on AWS. The data is in CSV format and will be queried using SQL. Which AWS service is most suitable for storing and querying this data?

Select 1 option(s):

Amazon RDS

Amazon Redshift Spectrum

Amazon S3

Amazon DynamoDB

Q48. A financial analytics firm requires a data storage solution to handle real-time analysis of stock market data. This solution must support high I/O throughput and low-latency read and write operations. Which AWS storage service is most appropriate?

Select 1 option(s):

Amazon RDS

Amazon EBS Provisioned IOPS SSD

Amazon S3

Amazon Redshift

Q49. A company requires a cost-effective solution to run a batch processing job that ingests historical data once a month from Amazon S3 into their data warehouse. The job is not time-sensitive. Which EC2 instance type is most appropriate for this scenario?

Select 1 option(s):

c5n.large

t3.medium

p3.2xlarge

Q50. An IoT company needs to ingest and process large volumes of data from thousands of sensors in real-time. The data will be used for immediate analysis and decision-making. Which AWS service would be the most appropriate for this requirement?

Select 1 option(s):

Amazon DynamoDB

Amazon Kinesis Data Firehose

AWS Glue

Amazon Redshift

Q51. A company wants to process and transform data from an Amazon S3 bucket each time a new file is uploaded. The processing needs to be lightweight and occur in real-time. Which AWS service is most suitable for this requirement?

Select 1 option(s):

Amazon EC2

Amazon Redshift

AWS Lambda

Amazon Kinesis Data Streams

Q52. A data engineering team is designing a system to process a continuous stream of data from IoT devices. The system must track the state of each device over time to detect anomalies. Which approach is most suitable for this requirement?

Select 1 option(s):

Stateless transactions using AWS Lambda

Stateful processing using Amazon Kinesis Data Analytics

Stateless transactions using Amazon S3

Stateful processing using Amazon EC2

Q53. A company is using Amazon Redshift for data warehousing. The security policy mandates the use of password-based authentication for all data analysts accessing the warehouse. What is the standard method to enforce this policy?

Select 1 option(s):

Enable Amazon Redshift to integrate with AWS IAM for password-based authentication.

Create individual database user accounts in Redshift with passwords for each data analyst.

Implement Amazon QuickSight with password authentication for accessing Redshift.

Use AWS Key Management Service (KMS) to manage password policies for Redshift users.

Q54. A team is using Amazon RDS to host their relational database. They need to perform a critical update on a particular table and want to ensure that no other transactions can access or modify this table during the update. What should they implement in Amazon RDS to manage locks and prevent access to this table?

Select 1 option(s):

Enable Multi-AZ deployments for RDS.

Use RDS Read Replicas.

Apply row-level security in RDS.

Use explicit table locks in the database.

Q55. A company needs to batch ingest data from a large number of IoT devices into an Amazon S3 bucket every 6 hours. The data should be encrypted at rest. Which configuration option should they use to ensure data security during the batch ingestion process?

Select 1 option(s):

Enable server-side encryption with Amazon S3-Managed Keys (SSE-S3) on the S3 bucket.

Use AWS KMS-managed keys (SSE-KMS) for client-side encryption.

Configure AWS Lambda for data encryption before ingestion.

Implement Amazon EC2-based encryption prior to S3 ingestion.

Q56. A data engineering team is analyzing customer data stored in an Amazon S3 bucket. They noticed that some records contain null values in critical fields, which could impact data quality. Which AWS service should they use to cleanse this data by identifying and addressing the null values?

Select 1 option(s):

AWS Glue DataBrew

Amazon Redshift

Amazon Athena

AWS Data Pipeline

Q57. A healthcare organization wants to process and analyze large volumes of unstructured medical data. The data needs to be converted into a structured format for further analytics and reporting. Which combination of AWS services should be used for processing and analyzing this data?

Select 1 option(s):

Amazon Kinesis Data Firehose and Amazon Redshift

Amazon EMR and Amazon Athena

Amazon S3 and Amazon QuickSight

AWS Lambda and Amazon DynamoDB

Q58. A financial institution requires a managed database service to handle high-volume transactional workloads with automatic scaling, backup, and high availability features. The database should also provide consistent and fast performance for transaction processing. Which AWS service should be used?

Select 1 option(s):

Amazon DynamoDB

Amazon RDS

Amazon Redshift

Amazon S3

Q59. A pharmaceutical company needs to integrate and organize various types of research data, including clinical trials, patient records, and genomic data, into a centralized data repository. The solution should facilitate secure data sharing, governance, and allow for scalable analytics. Which AWS service best fits these requirements?

Select 1 option(s):

Amazon RDS

Amazon Redshift

Amazon DynamoDB

AWS Lake Formation

Q60. A media company needs to process high volumes of streaming video data in real-time for analytics and immediate decision-making. The solution should handle large-scale data streams and provide low-latency data processing. Which AWS service is most suitable for this scenario?

Select 1 option(s):

Amazon Kinesis Data Streams

Amazon S3

Amazon Redshift

Amazon RDS

Free AWS Certified Data Engineer (DEA-C01) Practice Test 12

Q1. A data engineering team needs to aggregate large volumes of web traffic data stored in Amazon S3 and generate summarized reports on a daily basis. The solution should optimize for query performance and cost. Which AWS service or combination of services is most suitable for this task?

Q2. In an effort to enhance data quality, a team is using AWS Glue DataBrew to clean a large dataset. They need to standardize the formatting of date fields which are currently in various formats. What is the most effective method to accomplish this in AWS Glue DataBrew?

Q3. A data engineering team needs to ensure secure access to an Amazon Redshift data warehouse. They want to restrict access to specific IP addresses from their corporate network. Which AWS feature should they use to configure this access control?

Q4. A company is setting up a data analysis environment on AWS. The data engineers require access to Amazon S3, Amazon Redshift, and AWS Glue. To manage permissions efficiently, what is the best approach for granting them the necessary access?

Q5. A data engineering team is building an application that requires connecting to a MySQL database and a Microsoft SQL Server database. Which connectivity method should they use to enable their application to interact with these different database systems?

Q6. A retail company needs to integrate sales data from its online store, hosted on Amazon RDS, with inventory data from a third-party system, accessible via an API. The integrated data will then be used for analytics. Which AWS service is most suitable for integrating these disparate data sources?

Q8. An enterprise plans to deploy a customer relationship management (CRM) system that requires a relational database with high availability, multi-region read replicas, and the ability to scale computing and storage resources independently. Which AWS service best fits these requirements?

Q9. A data engineer is required to create an SQL query to list all products, their prices, and the names of the categories they belong to. The relevant tables are Products and Categories, linked by the CategoryID field. Which query would correctly accomplish this task?

Q10. During the execution of an AWS Glue ETL job, a data engineer notices that the job is taking significantly longer than expected to complete. What should be the first step in troubleshooting this performance issue?

Q11. A company is performing complex data transformations and analytics on a large dataset using Apache Spark. They need to ensure high availability and fault tolerance for their Spark application. What feature of Apache Spark should they primarily leverage to achieve this?

Q12. A company is developing a new web application that requires a relational database with the ability to handle complex queries and joins. The database should also be cost-effective and offer features like automated backups and easy scaling. Which AWS service meets these requirements?

Q14. An organization requires a solution to analyze streaming data in real-time from multiple sources. The solution must be able to handle large-scale data processing and provide the flexibility to use various big data frameworks. Which AWS service is most appropriate for this scenario?

Q15. A data engineering team is tasked with integrating external data sources into their data lake on AWS. They want to consume data from external APIs and ensure that the data is regularly updated in their data lake. Which AWS service should the team use to achieve this?

Q16. A team is deploying AWS infrastructure using AWS CloudFormation. They need to ensure that CloudFormation has the necessary permissions to create, update, and delete resources as specified in the templates. Which approach should they take to provide these permissions?

Q18. An e-commerce company wants to build a system for processing user activity and clickstream data in real-time to provide personalized shopping experiences. The system must be able to handle large-scale and high-velocity data streams. Which AWS service is most suitable for this use case?

Q19. A company needs to analyze large volumes of data from various sources and perform complex queries. The solution should be cost-effective while offering high-performance analytics. Which AWS service aligns best with these requirements?

Q21. A new application deployed on AWS requires different levels of access to AWS resources for various components. What is the recommended approach to manage these access levels effectively?

Q23. A company is deploying an AWS Lambda function that needs to read data from an Amazon S3 bucket and write logs to Amazon CloudWatch. Which of the following is the most appropriate way to set up IAM roles for this Lambda function?

Q25. A company is using Amazon API Gateway for its serverless application. They want to ensure that only certain AWS services, like AWS Lambda and Amazon S3, can invoke the API. What is the recommended way to configure access control for this scenario?

Q27. A data engineering team wants to automatically trigger an AWS Lambda function for data processing every day at midnight. The process should integrate with other AWS services for additional tasks. Which AWS service should be used to schedule and trigger this daily event?

Q28. A media company is streaming a mix of structured and unstructured data, including video metadata and user interaction logs, for real-time analysis. The solution must handle large volumes of data at high velocity. Which AWS service is best suited for this scenario?

Q29. An organization using AWS needs to ensure that their EC2 instances can access specific AWS services like Amazon S3 and Amazon DynamoDB without storing access keys on the instances. What is the recommended method to securely manage this access?

Q31. A data engineering team is using Amazon Redshift for their data warehousing needs. They need to ensure that a specific set of data is not modified during a critical analysis period. Which method should they use to manage locks and prevent modification of this data in Amazon Redshift?

Q32. A company is developing an application that requires real-time ingestion of data from a social media platforms API. The ingested data will be used for immediate sentiment analysis. Which AWS service combination is most suitable for consuming the API and performing the analysis?

Q33. A data engineering team needs to ensure that the data stored in HDFS on Amazon EMR is encrypted at rest. Which of the following is the most appropriate solution to meet this requirement?

Q34. A data engineer is developing an application that needs to interact with Amazon S3 to store and retrieve data. The engineer is using Python for application development. Which AWS service should the engineer use to call SDKs and access Amazon S3 features from the Python code?

Q37. A company needs to automate the execution of an AWS Glue ETL job to process data daily at midnight. Which AWS service should be used to schedule and trigger this ETL job?

Q38. A data engineer is setting up access to an Amazon RDS database for application users. The requirement is to use password-based authentication for these users. Which of the following approaches should the engineer take to implement this?

Q40. An organization is using Amazon EMR for their big data processing needs. They require that all data in transit within the EMR cluster be encrypted to comply with their strict data security policies. Which of the following methods should be used to achieve this requirement?

Q41. A financial institution is using Amazon RDS for their database needs. They need to ensure that data transferred between their application servers and the RDS database is encrypted during transit. Which option should they configure to enable encryption in transit for RDS effectively?

Q42. A data engineer needs to choose between AWS managed database service Amazon RDS and self-managed databases on Amazon EC2 instances. What is a primary difference regarding the authentication mechanisms between these two services?

Q43. A financial services company is setting up a system to process high-volume, real-time stock market data for immediate analysis. Which AWS service is most suitable for reading and processing this type of streaming data?

Q44. A company needs to ingest historical log data stored in Amazon S3 into a data warehouse for analysis. The data ingestion process is required to happen on a weekly basis. Which AWS service is most appropriate for this data ingestion pattern?

Q45. An enterprise intends to analyze its operational data stored in Parquet format using serverless computing. The analysis requires fast query performance and the ability to handle complex queries. Which combination of AWS services should be used?

Q47. Your company plans to store a large dataset of historical sales data in a data lake on AWS. The data is in CSV format and will be queried using SQL. Which AWS service is most suitable for storing and querying this data?

Q48. A financial analytics firm requires a data storage solution to handle real-time analysis of stock market data. This solution must support high I/O throughput and low-latency read and write operations. Which AWS storage service is most appropriate?

Q49. A company requires a cost-effective solution to run a batch processing job that ingests historical data once a month from Amazon S3 into their data warehouse. The job is not time-sensitive. Which EC2 instance type is most appropriate for this scenario?

Q50. An IoT company needs to ingest and process large volumes of data from thousands of sensors in real-time. The data will be used for immediate analysis and decision-making. Which AWS service would be the most appropriate for this requirement?

Q51. A company wants to process and transform data from an Amazon S3 bucket each time a new file is uploaded. The processing needs to be lightweight and occur in real-time. Which AWS service is most suitable for this requirement?

Q52. A data engineering team is designing a system to process a continuous stream of data from IoT devices. The system must track the state of each device over time to detect anomalies. Which approach is most suitable for this requirement?

Q53. A company is using Amazon Redshift for data warehousing. The security policy mandates the use of password-based authentication for all data analysts accessing the warehouse. What is the standard method to enforce this policy?

Q55. A company needs to batch ingest data from a large number of IoT devices into an Amazon S3 bucket every 6 hours. The data should be encrypted at rest. Which configuration option should they use to ensure data security during the batch ingestion process?

Q56. A data engineering team is analyzing customer data stored in an Amazon S3 bucket. They noticed that some records contain null values in critical fields, which could impact data quality. Which AWS service should they use to cleanse this data by identifying and addressing the null values?

Q57. A healthcare organization wants to process and analyze large volumes of unstructured medical data. The data needs to be converted into a structured format for further analytics and reporting. Which combination of AWS services should be used for processing and analyzing this data?

Q60. A media company needs to process high volumes of streaming video data in real-time for analytics and immediate decision-making. The solution should handle large-scale data streams and provide low-latency data processing. Which AWS service is most suitable for this scenario?

Q32. A company is developing an application that requires real-time ingestion of data from a social media platforms API. The ingested data will be used for immediate sentiment analysis. Which AWS service combination is most suitable for consuming the API and performing the analysis?