Amazon DATA-ENGINEER-ASSOCIATE Online Practice Questions and Exam Preparation

Amazon DATA-ENGINEER-ASSOCIATE Online Questions & Answers

• Question 311:

  A company runs a data platform on AWS.

  The data platform uses AWS Glue to provide a data catalog and to perform processing.

  The company notices quality issues in the data.

  The company needs to implement data quality validations.

  The validations must include rules for known issues.

  The validations must have the ability to automatically detect unexpected data quality issues.

  Which solution will meet these requirements with the LEAST operation overhead?

  A. Use AWS Glue jobs to implement AWS Glue Data Quality validations that include anomaly detection.
  B. Use AWS Glue jobs to implement data quality rules that use open source data quality frameworks.
  C. Use AWS Glue DataBrew to profile the data. Configure data quality rules based on the data quality results from the profiling.
  D. Use AWS Glue jobs to implement data quality validations that use SQL statements.
  A. Use AWS Glue jobs to implement AWS Glue Data Quality validations that include anomaly detection.

• Question 312:

  A company has AWS resources in multiple AWS Regions. The company has an Amazon EFS file system in each Region where the company operates. The company's data science team operates within only a single Region. The data that the data science team works with must remain within the team's Region.

  A data engineer needs to create a single dataset by processing les that are in each of the company's Regional EFS file systems. The data engineer wants to use an AWS Step Functions state machine to orchestrate AWS Lambda functions to process the data.

  Which solution will meet these requirements with the LEAST effort?

  A. Peer the VPCs that host the EFS file systems in each Region with the VPC that is in the data science team's Region. Enable EFS file locking. configure the Lambda functions in the data science team's Region to mount each of the Region specific file systems. Use the Lambda functions to process the data.
  B. configure each of the Regional EFS file systems to replicate data to the data science team's Region. In the data science team's Region, configure the Lambda functions to mount the replica file systems. Use the Lambda functions to process the data.
  C. Deploy the Lambda functions to each Region. Mount the Regional EFS file systems to the Lambda functions. Use the Lambda functions to process the data. Store the output in an Amazon S3 bucket in the data science team's Region.
  D. Use AWS DataSync to transfer les from each of the Regional EFS les systems to the file system that is in the data science team's Region. configure the Lambda functions in the data science team's Region to mount the file system that is in the same Region. Use the Lambda functions to process the data.
  D. Use AWS DataSync to transfer les from each of the Regional EFS les systems to the file system that is in the data science team's Region. configure the Lambda functions in the data science team's Region to mount the file system that is in the same Region. Use the Lambda functions to process the data.

• Question 313:

  A company uses Amazon RDS to store transactional data. The company runs an RDS DB instance in a private subnet. A developer wrote an AWS Lambda function with default settings to insert, update, or delete data in the DB instance.

  The developer needs to give the Lambda function the ability to connect to the DB instance privately without using the public internet.

  Which combination of steps will meet this requirement with the LEAST operational overhead? (Choose two.)

  A. Turn on the public access setting for the DB instance.
  B. Update the security group of the DB instance to allow only Lambda function invocations on the database port.
  C. Configure the Lambda function to run in the same subnet that the DB instance uses.
  D. Attach the same security group to the Lambda function and the DB instance. Include a self-referencing rule that allows access through the database port.
  E. Update the network ACL of the private subnet to include a self-referencing rule that allows access through the database port.
  C. Configure the Lambda function to run in the same subnet that the DB instance uses.
  D. Attach the same security group to the Lambda function and the DB instance. Include a self-referencing rule that allows access through the database port.

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  Explanation

  To enable the Lambda function to connect to the RDS DB instance privately without using the public internet, the best combination of steps is to configure the Lambda function to run in the same subnet that the DB instance uses, and attach the same security group to the Lambda function and the DB instance.

  This way, the Lambda function and the DB instance can communicate within the same private network, and the security group can allow traffic between them on the database port. This solution has the least operational overhead, as it does not require any changes to the public access setting, the network ACL, or the security group of the DB instance.

  The other options are not optimal for the following reasons:

  A. Turn on the public access setting for the DB instance. This option is not recommended, as it would expose the DB instance to the public internet, which can compromise the security and privacy of the data. Moreover, this option would not enable the Lambda function to connect to thTo enable the Lambda function to connect to the RDS DB instance privately without using the public internet, the best combination of steps is to configure the Lambda function to run in the same subnet that the DB instance uses, and attach the same security group to the Lambda function and the DB instance. This way, the Lambda function and the DB instance can communicate within the same private network, and the security group can allow traffic between them on the database port. This solution has the least operational overhead, as it does not require any changes to the public access setting, the network ACL, or the security group of the DB instance. The other options are not optimal for the following reasons: Option A: Turn on the public access setting for the DB instance. This option is not recommended, as it would expose the DB instance to the public internet, which can compromise the security and privacy of the data. Moreover, this option would not enable the Lambda function to connect to the DB instance privately, as it would still require the Lambda function to use the public internet to access the DB instance. Option B: Update the security group of the DB instance to allow only Lambda function invocations on the database port. This option is not sufficient, as it would only modify the inbound rules of the security group of the DB instance, but not the outbound rules of the security group of the Lambda function. Moreover, this option would not enable the Lambda function to connect to the DB instance privately, as it would still require the Lambda function to use the public internet to access the DB instance. Option E: Update the network ACL of the private subnet to include a self-referencing rule that allows access through the database port. This option is not necessary, as the network ACL of the private subnet already allows all traffic within the subnet by default. Moreover, this option would not enable the Lambda function to connect to the DB instance privately, as it would still require the Lambda function to use the public internet to access the DB instance.

  References:

  1: Connecting to an Amazon RDS DB instance

  2: Configuring a Lambda function to access resources in a VPC

  3: Working with security groups Network ACLse DB instance privately, as it would still require the Lambda function to use the public internet to access the DB instance.

  B. Update the security group of the DB instance to allow only Lambda function invocations on the database port. This option is not sufficient, as it would only modify the inbound rules of the security group of the DB instance, but not the outbound rules of the security group of the Lambda function. Moreover, this option would not enable the Lambda function to connect to the DB instance privately, as it would still require the Lambda function to use the public internet to access the DB instance.

  E. Update the network ACL of the private subnet to include a self-referencing rule that allows access through the database port. This option is not necessary, as the network ACL of the private subnet already allows all traffic within the subnet by default. Moreover, this option would not enable the Lambda function to connect to the DB instance privately, as it would still require the Lambda function to use the public internet to access the DB instance.

• Question 314:

  A company is using an AWS Transfer Family server to migrate data from an on-premises environment to AWS. Company policy mandates the use of TLS 1.2 or above to encrypt the data in transit.

  Which solution will meet these requirements?

  A. Generate new SSH keys for the Transfer Family server. Make the old keys and the new keys available for use.
  B. Update the security group rules for the on-premises network to allow only connections that use TLS 1.2 or above.
  C. Update the security policy of the Transfer Family server to specify a minimum protocol version of TLS 1.2.
  D. Install an SSL certificate on the Transfer Family server to encrypt data transfers by using TLS 1.2.
  C. Update the security policy of the Transfer Family server to specify a minimum protocol version of TLS 1.2.

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  Explanation

  The AWS Transfer Family server's security policy can be updated to enforce TLS 1.2 or higher, ensuring compliance with company policy for encrypted data transfers.

  AWS Transfer Family Security Policy:

  AWS Transfer Family supports setting a minimum TLS version through its security policy configuration.

  This ensures that only connections using TLS 1.2 or above are allowed.

• Question 315:

  A company plans to provision a log delivery stream within a VPC. The company configured the VPCflow logs to publish to Amazon CloudWatch Logs. The company needs to send theflow logs to Splunk in near real time for further analysis.

  Which solution will meet these requirements with the LEAST operational overhead?

  A. Configure an Amazon Kinesis Data Streams data stream to use Splunk as the destination. Create a CloudWatch Logs subscription filter to send log events to the data stream.
  B. Create an Amazon Kinesis Data Firehose delivery stream to use Splunk as the destination. Create a CloudWatch Logs subscription filter to send log events to the delivery stream.
  C. Create an Amazon Kinesis Data Firehose delivery stream to use Splunk as the destination. Create an AWS Lambda function to send the flow logs from CloudWatch Logs to the delivery stream.
  D. Configure an Amazon Kinesis Data Streams data stream to use Splunk as the destination. Create an AWS Lambda function to send the flow logs from CloudWatch Logs to the data stream.
  B. Create an Amazon Kinesis Data Firehose delivery stream to use Splunk as the destination. Create a CloudWatch Logs subscription filter to send log events to the delivery stream.

• Question 316:

  A data engineer maintains custom Python scripts that perform a data formatting process that many AWS Lambda functions use. When the data engineer needs to modify the Python scripts, the data engineer must manually update all the Lambda functions.

  The data engineer requires a less manual way to update the Lambda functions.

  Which solution will meet this requirement?

  A. Store a pointer to the custom Python scripts in the execution context object in a shared Amazon S3 bucket.
  B. Package the custom Python scripts into Lambda layers. Apply the Lambda layers to the Lambda functions.
  C. Store a pointer to the custom Python scripts in environment variables in a shared Amazon S3 bucket.
  D. Assign the same alias to each Lambda function. Call reach Lambda function by specifying the function's alias.
  B. Package the custom Python scripts into Lambda layers. Apply the Lambda layers to the Lambda functions.

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  Explanation

  Lambda layers are a way to share code and dependencies across multiple Lambda functions. By packaging the custom Python scripts into Lambda layers, the data engineer can update the scripts in one place and have them automatically applied to all the Lambda functions that use the layer. This reduces the manual effort and ensures consistency across the Lambda functions. The other options are either not feasible or not efficient. Storing a pointer to the custom Python scripts in the execution context object or in environment variables would require the Lambda functions to download the scripts from Amazon S3 every time they are invoked, which would increase latency and cost. Assigning the same alias to each Lambda function would not help with updating the Python scripts, as the alias only points to a specific version of the Lambda function code.

  References:

  AWS Lambda layers

  AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 3: Data Ingestion and Transformation, Section 3.4: AWS Lambda

• Question 317:

  A financial services company stores financial data in Amazon Redshift. A data engineer wants to run real-time queries on the financial data to support a web-based trading application. The data engineer wants to run the queries from within the trading application.

  Which solution will meet these requirements with the LEAST operational overhead?

  A. Establish WebSocket connections to Amazon Redshift.
  B. Use the Amazon Redshift Data API.
  C. Set up Java Database Connectivity (JDBC) connections to Amazon Redshift.
  D. Store frequently accessed data in Amazon S3. Use Amazon S3 Select to run the queries.
  B. Use the Amazon Redshift Data API.

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  Explanation

  The Amazon Redshift Data API is a built-in feature that allows you to run SQL queries on Amazon Redshift data with web services-based applications, such as AWS Lambda, Amazon SageMaker notebooks, and AWS Cloud. The Data API does not require a persistent connection to your database, and it provides a secure HTTP endpoint and integration with AWS SDKs. You can use the endpoint to run SQL statements without managing connections. The Data API also supports both Amazon Redshift provisioned clusters and Redshift Serverless workgroups. The Data API is the best solution for running real-time queries on the financial data from within the trading application, as it has the least operational overhead compared to the other options.

  Option A is not the best solution, as establishing WebSocket connections to Amazon Redshift would require more configuration and maintenance than using the Data API. WebSocket connections are also not supported by Amazon Redshift clusters or serverless workgroups.

  Option C is not the best solution, as setting up JDBC connections to Amazon Redshift would also require more configuration and maintenance than using the Data API. JDBC connections are also not supported by Redshift Serverless workgroups.

  Option D is not the best solution, as storing frequently accessed data in Amazon S3 and using Amazon S3 Select to run the queries would introduce additional latency and complexity than using the Data API.

  Amazon S3 Select is also not optimized for real-time queries, as it scans the entire object before returning the results.

• Question 318:

  A company uses an Amazon Redshift cluster to manage data, including vendor sales data. The company wants to store a copy of the vendor data in an Amazon S3 bucket.

  A data engineer sets up an AWS Glue job to upload the data to the S3 bucket data on a schedule. The data engineer set up a network connection to allow private traffic between Amazon Redshift and Amazon

  S3.

  What is the next step required to meet this requirement?

  A. Create an IAM role that has permission to write to the S3 bucket. Associate the IAM role with the Amazon Redshift cluster.
  B. Add the S3 bucket to an AWS Glue Data Catalog. Configure Amazon Redshift Spectrum to access the Data Catalog.
  C. Enable the Amazon Redshift data sharing feature. Set the S3 bucket as a target bucket for data sharing.
  D. Store login credentials for Amazon Redshift in AWS Secrets Manager. Add a reference to the secret to the Glue job configuration.
  A. Create an IAM role that has permission to write to the S3 bucket. Associate the IAM role with the Amazon Redshift cluster.

• Question 319:

  A company receives marketing campaign data from a vendor. The company ingests the data into an Amazon S3 bucket every 40 to 60 minutes. The data is in CSV format. File sizes are between 100 KB and 300 KB.

  A data engineer needs to set-up an extract, transform, and load (ETL) pipeline to upload the content of each file to Amazon Redshift.

  Which solution will meet these requirements with the LEAST operational overhead?

  A. Create an AWS Lambda function that connects to Amazon Redshift and runs a COPY command. Use Amazon EventBridge to invoke the Lambda function based on an Amazon S3 upload trigger.
  B. Create an Amazon Data Firehose stream. Configure the stream to use an AWS Lambda function as a source to pull data from the S3 bucket. Set Amazon Redshift as the destination.
  C. Use Amazon Redshift Spectrum to query the S3 bucket. Configure an AWS Glue Crawler for the S3 bucket to update metadata in an AWS Glue Data Catalog.
  D. Creates an AWS Database Migration Service (AWS DMS) task. Specify an appropriate data schema to migrate. Specify the appropriate type of migration to use.
  A. Create an AWS Lambda function that connects to Amazon Redshift and runs a COPY command. Use Amazon EventBridge to invoke the Lambda function based on an Amazon S3 upload trigger.

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  Explanation

  Configuring your S3 bucket to emit "Object Created" events into EventBridge and using a rule to invoke a lightweight Lambda function lets you automatically run a Redshift COPY for each new CSV. This serverle, event-driven pattern requires no continuously running infrastructure and has minimal operational overhead.

• Question 320:

  A company is planning to migrate on-premises Apache Hadoop clusters to Amazon EMR. The company also needs to migrate a data catalog into a persistent storage solution.

  The company currently stores the data catalog in an on-premises Apache Hive metastore on the Hadoop clusters. The company requires a serverless solution to migrate the data catalog.

  Which solution will meet these requirements MOST cost-effectively?

  A. Use AWS Database Migration Service (AWS DMS) to migrate the Hive metastore into Amazon S3. Configure AWS Glue Data Catalog to scan Amazon S3 to produce the data catalog.
  B. Configure a Hive metastore in Amazon EMR. Migrate the existing on-premises Hive metastore into Amazon EMR. Use AWS Glue Data Catalog to store the company's data catalog as an external data catalog.
  C. Configure an external Hive metastore in Amazon EMR. Migrate the existing on-premises Hive metastore into Amazon EMR. Use Amazon Aurora MySQL to store the company's data catalog.
  D. Configure a new Hive metastore in Amazon EMR. Migrate the existing on-premises Hive metastore into Amazon EMR. Use the new metastore as the company's data catalog.
  B. Configure a Hive metastore in Amazon EMR. Migrate the existing on-premises Hive metastore into Amazon EMR. Use AWS Glue Data Catalog to store the company's data catalog as an external data catalog.