Quiz IT certification exam

Question 1

A company stores datasets in JSON format and .csv format in an Amazon S3 bucket. The company has Amazon RDS for Microsoft SQL Server databases, Amazon DynamoDB tables that are in provisioned capacity mode, and an Amazon Redshift cluster. A data engineering team must develop a solution that will give data scientists the ability to query all data sources by using syntax similar to SQL.

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

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Accepted Answer

Use AWS Glue to crawl the data sources. Store metadata in the AWS Glue Data Catalog. Use Amazon Athena to query the data. Use SQL for structured data sources. Use PartiQL for data that is stored in JSON format.

Answer

Use AWS Glue to crawl the data sources. Store metadata in the AWS Glue Data Catalog. Use Redshift Spectrum to query the data. Use SQL for structured data sources. Use PartiQL for data that is stored in JSON format.

Answer

Use AWS Glue to crawl the data sources. Store metadata in the AWS Glue Data Catalog. Use AWS Glue jobs to transform data that is in JSON format to Apache Parquet or .csv format. Store the transformed data in an S3 bucket. Use Amazon Athena to query the original and transformed data from the S3 bucket.

Answer

Use AWS Lake Formation to create a data lake. Use Lake Formation jobs to transform the data from all data sources to Apache Parquet format. Store the transformed data in an S3 bucket. Use Amazon Athena or Redshift Spectrum to query the data.

Question 2

A data engineer is configuring Amazon SageMaker Studio to use AWS Glue interactive sessions to prepare data for machine learning (ML) models.The data engineer receives an access denied error when the data engineer tries to prepare the data by using SageMaker Studio.Which change should the engineer make to gain access to SageMaker Studio?

Accepted Answer

Add a policy to the data engineer's IAM user that includes the sts:AssumeRole action for the AWS Glue and SageMaker service principals in the trust policy.

Answer

Add the AWSGlueServiceRole managed policy to the data engineer's IAM user.

Answer

Add the AmazonSageMakerFullAccess managed policy to the data engineer's IAM user.

Answer

Add a policy to the data engineer's IAM user that allows the sts:AddAssociation action for the AWS Glue and SageMaker service principals in the trust policy.

Question 3

A company extracts approximately 1 TB of data every day from data sources such as SAP HANA, Microsoft SQL Server, MongoDB, Apache Kafka, and Amazon DynamoDB. Some of the data sources have undefined data schemas or data schemas that change.A data engineer must implement a solution that can detect the schema for these data sources. The solution must extract, transform, and load the data to an Amazon S3 bucket. The company has a service level agreement (SLA) to load the data into the S3 bucket within 15 minutes of data creation.Which solution will meet these requirements with the LEAST operational overhead?

Accepted Answer

Use AWS Glue to detect the schema and to extract, transform, and load the data into the S3 bucket. Create a pipeline in Apache Spark.

Answer

Use Amazon EMR to detect the schema and to extract, transform, and load the data into the S3 bucket. Create a pipeline in Apache Spark.

Answer

Create a PvSpark proqram in AWS Lambda to extract, transform, and load the data into the S3 bucket.

Answer

Create a stored procedure in Amazon Redshift to detect the schema and to extract, transform, and load the data into a Redshift Spectrum table. Access the table from Amazon S3.

Question 4

A company has multiple applications that use datasets that are stored in an Amazon S3 bucket. The company has an ecommerce application that generates a dataset that contains personally identifiable information (PII). The company has an internal analytics application that does not require access to the PII.To comply with regulations, the company must not share PII unnecessarily. A data engineer needs to implement a solution that with redact PII dynamically, based on the needs of each application that accesses the dataset.Which solution will meet the requirements with the LEAST operational overhead?

Accepted Answer

Create an S3 Object Lambda endpoint. Use the S3 Object Lambda endpoint to read data from the S3 bucket. Implement redaction logic within an S3 Object Lambda function to dynamically redact PII based on the needs of each application that accesses the data.

Answer

Create an S3 bucket policy to limit the access each application has. Create multiple copies of the dataset. Give each dataset copy the appropriate level of redaction for the needs of the application that accesses the copy.

Answer

Use AWS Glue to transform the data for each application. Create multiple copies of the dataset. Give each dataset copy the appropriate level of redaction for the needs of the application that accesses the copy.

Answer

Create an API Gateway endpoint that has custom authorizers. Use the API Gateway endpoint to read data from the S3 bucket. Initiate a REST API call to dynamically redact PII based on the needs of each application that accesses the data.

Question 5

A data engineer needs to build an extract, transform, and load (ETL) job. The ETL job will process daily incoming .csv files that users upload to an Amazon S3 bucket. The size of each S3 object is less than 100 MB.Which solution will meet these requirements MOST cost-effectively?

Accepted Answer

Write an AWS Glue Python shell job. Use pandas to transform the data.

Answer

Write a custom Python application. Host the application on an Amazon Elastic Kubernetes Service (Amazon EKS) cluster.

Answer

Write a PySpark ETL script. Host the script on an Amazon EMR cluster.

Answer

Write an AWS Glue PySpark job. Use Apache Spark to transform the data.

Question 6

The company stores a large volume of customer records in Amazon S3. To comply with regulations, the company must be able to access new customer records immediately for the first 30 days after the records are created. The company accesses records that are older than 30 days infrequently.The company needs to cost-optimize its Amazon S3 storage.Which solution will meet these requirements MOST cost-effectively?

Accepted Answer

Apply a lifecycle policy to transition records to S3 Standard Infrequent-Access (S3 Standard-IA) storage after 30 days.

Answer

Use S3 Intelligent-Tiering storage.

Answer

Transition records to S3 Glacier Deep Archive storage after 30 days.

Answer

Use S3 Standard-Infrequent Access (S3 Standard-IA) storage for all customer records.

Question 7

A retail company is expanding its operations globally. The company needs to use Amazon QuickSight to accurately calculate currency exchange rates for financial reports. The company has an existing dashboard that includes a visual that is based on an analysis of a dataset that contains global currency values and exchange rates.A data engineer needs to ensure that exchange rates are calculated with a precision of four decimal places. The calculations must be precomputed. The data engineer must materialize results in QuickSight super-fast, parallel, in-memory calculation engine (SPICE).Which solution will meet these requirements?

Accepted Answer

Define and create the calculated field in the dataset.

Answer

Define and create the calculated field in the analysis.

Answer

Define and create the calculated field in the visual.

Answer

Define and create the calculated field in the dashboard.

Question 8

A retail company uses an Amazon Redshift data warehouse and an Amazon S3 bucket. The company ingests retail order data into the S3 bucket every day.The company stores all order data at a single path within the S3 bucket. The data has more than 100 columns. The company ingests the order data from a third-party application that generates more than 30 files in CSV format every day. Each CSV file is between 50 and 70 MB in size.The company uses Amazon Redshift Spectrum to run queries that select sets of columns. Users aggregate metrics based on daily orders. Recently, users have reported that the performance of the queries has degraded. A data engineer must resolve the performance issues for the queries.Which combination of steps will meet this requirement with LEAST developmental effort? (Select TWO.)

Accepted Answer

Configure the third-party application to create the files in a columnar format.

Accepted Answer

Partition the order data in the S3 bucket based on order date.

Answer

Develop an AWS Glue ETL job to convert the multiple daily CSV files to one file for each day.

Answer

Configure the third-party application to create the files in JSON format.

Answer

Load the JSON data into the Amazon Redshift table in a SUPER type column.

Question 9

A company ingests data from multiple data sources and stores the data in an Amazon S3 bucket. An AWS Glue extract, transform, and load (ETL) job transforms the data and writes the transformed data to an Amazon S3 based data lake. The company uses Amazon Athena to query the data that is in the data lake.The company needs to identify matching records even when the records do not have a common unique identifier.Which solution will meet this requirement?

Accepted Answer

Train and use the AWS Lake Formation FindMatches transform in the ETL job.

Answer

Use Amazon Made pattern matching as part of the ETL job.

Answer

Train and use the AWS Glue PySpark Filter class in the ETL job.

Answer

Partition tables and use the ETL job to partition the data on a unique identifier.

Question 10

A company stores its processed data in an S3 bucket. The company has a strict data access policy. The company uses IAM roles to grant teams within the company different levels of access to the S3 bucket.The company wants to receive notifications when a user violates the data access policy. Each notification must include the username of the user who violated the policy.Which solution will meet these requirements?

Accepted Answer

Use AWS CloudTrail to track object-level events for the S3 bucket. Forward events to Amazon CloudWatch to set up CloudWatch alarms.

Answer

Use AWS Config rules to detect violations of the data access policy. Set up compliance alarms.

Answer

Use Amazon CloudWatch metrics to gather object-level metrics. Set up CloudWatch alarms.

Answer

Use Amazon S3 server access logs to monitor access to the bucket. Forward the access logs to an Amazon CloudWatch log group. Use metric filters on the log group to set up CloudWatch alarms.

Question 11

A company stores logs in an Amazon S3 bucket. When a data engineer attempts to access several log files, the data engineer discovers that some files have been unintentionally deleted.The data engineer needs a solution that will prevent unintentional file deletion in the future.Which solution will meet this requirement with the LEAST operational overhead?

Accepted Answer

Enable S3 Versioning for the S3 bucket.

Answer

Manually back up the S3 bucket on a regular basis.

Answer

Configure replication for the S3 bucket.

Answer

Use an Amazon S3 Glacier storage class to archive the data that is in the S3 bucket.

Question 12

A company currently uses a provisioned Amazon EMR cluster that includes general purpose Amazon EC2 instances. The EMR cluster uses EMR managed scaling between one to five task nodes for the company's long-running Apache Spark extract, transform, and load (ETL) job. The company runs the ETL job every day.When the company runs the ETL job, the EMR cluster quickly scales up to five nodes. The EMR cluster often reaches maximum CPU usage, but the memory usage remains under 30%.The company wants to modify the EMR cluster configuration to reduce the EMR costs to run the daily ETL job.Which solution will meet these requirements MOST cost-effectively?

Accepted Answer

Switch the task node type from general purpose EC2 instances to compute optimized EC2 instances.

Answer

Increase the maximum number of task nodes for EMR managed scaling to 10.

Answer

Change the task node type from general purpose EC2 instances to memory optimized EC2 instances.

Answer

Reduce the scaling cooldown period for the provisioned EMR cluster.

Question 13

A company is building a data stream processing application. The application runs in an Amazon Elastic Kubernetes Service (Amazon EKS) cluster. The application stores processed data in an Amazon DynamoDB table.The company needs the application containers in the EKS cluster to have secure access to the DynamoDB table. The company does not want to embed AWS credentials in the containers.Which solution will meet these requirements?

Accepted Answer

Attach an IAM role to the EKS worker nodes. Grant the IAM role access to DynamoDB. Use the IAM role to set up IAM roles service accounts (IRSA) functionality.

Answer

Store the AWS credentials in an Amazon S3 bucket. Grant the EKS containers access to the S3 bucket to retrieve the credentials.

Answer

Create an IAM user that has an access key to access the DynamoDB table. Use environment variables in the EKS containers to store the IAM user access key data.

Answer

Create an IAM user that has an access key to access the DynamoDB table. Use Kubernetes secrets that are mounted in a volume of the EKS cluster nodes to store the user access key data.

Question 14

A technology company currently uses Amazon Kinesis Data Streams to collect log data in real time. The company wants to use Amazon Redshift for downstream real-time queries and to enrich the log data.Which solution will ingest data into Amazon Redshift with the LEAST operational overhead?

Accepted Answer

Use Amazon Redshift streaming ingestion from Kinesis Data Streams and to present data as a materialized view.

Answer

Set up an Amazon Data Firehose delivery stream to send data to a Redshift provisioned cluster table.

Answer

Set up an Amazon Data Firehose delivery stream to send data to Amazon S3. Configure a Redshift provisioned cluster to load data every minute.

Answer

Configure Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to send data directly to a Redshift provisioned cluster table.

Question 15

A company has three subsidiaries. Each subsidiary uses a different data warehousing solution. The first subsidiary hosts its data warehouse in Amazon Redshift. The second subsidiary uses Teradata Vantage on AWS. The third subsidiary uses Google BigQuery.The company wants to aggregate all the data into a central Amazon S3 data lake. The company wants to use Apache Iceberg as the table format.A data engineer needs to build a new pipeline to connect to all the data sources, run transformations by using each source engine, join the data, and write the data to Iceberg.Which solution will meet these requirements with the LEAST operational effort?

Accepted Answer

Use the Amazon Athena federated query connectors for Amazon Redshift, Teradata, and BigQuery to build the pipeline in Athena. Write a SQL query to read from all the data sources, join the data, and run a Merge operation on the data lake Iceberg table.

Answer

Use native Amazon Redshift, Teradata, and BigQuery connectors to build the pipeline in AWS Glue. Use native AWS Glue transforms to join the data. Run a Merge operation on the data lake Iceberg table.

Answer

Use the native Amazon Redshift connector, the Java Database Connectivity (JDBC) connector for Teradata, and the open source Apache Spark BigQuery connector to build the pipeline in Amazon EMR. Write code in PySpark to join the data. Run a Merge operation on the data lake Iceberg table.

Answer

Use the native Amazon Redshift, Teradata, and BigQuery connectors in Amazon Appflow to write data to Amazon S3 and AWS Glue Data Catalog. Use Amazon Athena to join the data. Run a Merge operation on the data lake Iceberg table.

Question 16

A company has a data lake in Amazon S3. The company collects AWS CloudTrail logs for multiple applications. The company stores the logs in the data lake, catalogs the logs in AWS Glue, and partitions the logs based on the year. The company uses Amazon Athena to analyze the logs.Recently, customers reported that a query on one of the Athena tables did not return any data. A data engineer must resolve the issue.Which combination of troubleshooting steps should the data engineer take? (Select TWO.)

Accepted Answer

Confirm that Athena is pointing to the correct Amazon S3 location.

Accepted Answer

Use the MSCK REPAIR TABLE command.

Answer

Increase the query timeout duration.

Answer

Restart Athena.

Answer

Delete and recreate the problematic Athena table.

Question 17

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?

Accepted Answer

Update the security policy of the Transfer Family server to specify a minimum protocol version of TLS 1.2.

Answer

Generate new SSH keys for the Transfer Family server. Make the old keys and the new keys available for use.

Answer

Update the security group rules for the on-premises network to allow only connections that use TLS 1.2 or above.

Answer

Install an SSL certificate on the Transfer Family server to encrypt data transfers by using TLS 1.2.

Question 18

A data engineer configured an AWS Glue Data Catalog for data that is stored in Amazon S3 buckets. The data engineer needs to configure the Data Catalog to receive incremental updates.The data engineer sets up event notifications for the S3 bucket and creates an Amazon Simple Queue Service (Amazon SQS) queue to receive the S3 events.Which combination of steps should the data engineer take to meet these requirements with LEAST operational overhead? (Select TWO.)

Accepted Answer

Create an S3 event-based AWS Glue crawler to consume events from the SQS queue.

Accepted Answer

Use an AWS Lambda function to directly update the Data Catalog based on S3 events that the SQS queue receives.

Answer

Define a time-based schedule to run the AWS Glue crawler, and perform incremental updates to the Data Catalog.

Answer

Manually initiate the AWS Glue crawler to perform updates to the Data Catalog when there is a change in the S3 bucket.

Answer

Use AWS Step Functions to orchestrate the process of updating the Data Catalog based on 53 events that the SQS queue receives.

Question 19

A company uploads .csv files to an Amazon S3 bucket. The company's data platform team has set up an AWS Glue crawler to perform data discovery and to create the tables and schemas.An AWS Glue job writes processed data from the tables to an Amazon Redshift database. The AWS Glue job handles column mapping and creates the Amazon Redshift tables in the Redshift database appropriately.If the company reruns the AWS Glue job for any reason, duplicate records are introduced into the Amazon Redshift tables. The company needs a solution that will update the Redshift tables without duplicates.Which solution will meet these requirements?

Accepted Answer

Modify the AWS Glue job to copy the rows into a staging Redshift table. Add SQL commands to update the existing rows with new values from the staging Redshift table.

Answer

Modify the AWS Glue job to load the previously inserted data into a MySQL database. Perform an upsert operation in the MySQL database. Copy the results to the Amazon Redshift tables.

Answer

Use Apache Spark's DataFrame dropDuplicates() API to eliminate duplicates. Write the data to the Redshift tables.

Answer

Use the AWS Glue ResolveChoice built-in transform to select the value of the column from the most recent record.

Question 20

A financial company recently added more features to its mobile app. The new features required the company to create a new topic in an existing Amazon Managed Streaming for Apache Kafka (Amazon MSK) cluster.A few days after the company added the new topic, Amazon CloudWatch raised an alarm on the RootDiskUsed metric for the MSK cluster.How should the company address the CloudWatch alarm?

Accepted Answer

Expand the storage of the MSK broker. Configure the MSK cluster storage to expand automatically.

Answer

Expand the storage of the Apache ZooKeeper nodes.

Answer

Update the MSK broker instance to a larger instance type. Restart the MSK cluster.

Answer

Specify the Target-Volume-in-GiB parameter for the existing topic.

Question 21

A company hosts its applications on Amazon EC2 instances. The company must use SSL/TLS connections that encrypt data in transit to communicate securely with AWS infrastructure that is managed by a customer.A data engineer needs to implement a solution to simplify the generation, distribution, and rotation of digital certificates. The solution must automatically renew and deploy SSL/TLS certificates.Which solution will meet these requirements with the LEAST operational overhead?

Accepted Answer

Use AWS Certificate Manager (ACM).

Answer

Store self-managed certificates on the EC2 instances.

Answer

Implement custom automation scripts in AWS Secrets Manager.

Answer

Use Amazon Elastic Container Service (Amazon ECS) Service Connect.

Question 22

A company saves customer data to an Amazon S3 bucket. The company uses server-side encryption with AWS KMS keys (SSE-KMS) to encrypt the bucket. The dataset includes personally identifiable information (PII) such as social security numbers and account details.Data that is tagged as PII must be masked before the company uses customer data for analysis. Some users must have secure access to the PII data during the preprocessing phase. The company needs a low-maintenance solution to mask and secure the PII data throughout the entire engineering pipeline.Which combination of solutions will meet these requirements? (Select TWO.)

Accepted Answer

Use AWS Glue DataBrew to perform extract, transform, and load (ETL) tasks that mask the PII data before analysis.

Accepted Answer

Use AWS Identity and Access Management (IAM) to manage permissions and to control access to the PII data.

Answer

Use Amazon GuardDuty to monitor access patterns for the PII data that is used in the engineering pipeline.

Answer

Configure an Amazon Made discovery job for the S3 bucket.

Answer

Write custom scripts in an application to mask the PII data and to control access.

Question 23

A data engineer needs to onboard a new data producer into AWS. The data producer needs to migrate data products to AWS.The data producer maintains many data pipelines that support a business application. Each pipeline must have service accounts and their corresponding credentials. The data engineer must establish a secure connection from the data producer's on-premises data center to AWS. The data engineer must not use the public internet to transfer data from an on-premises data center to AWS.Which solution will meet these requirements?

Accepted Answer

Create an AWS Direct Connect connection to the on-premises data center. Store the service account credentials in AWS Secrets manager.

Answer

Instruct the new data producer to create Amazon Machine Images (AMIs) on Amazon Elastic Container Service (Amazon ECS) to store the code base of the application. Create security groups in a public subnet that allow connections only to the on-premises data center.

Answer

Create a security group in a public subnet. Configure the security group to allow only connections from the CIDR blocks that correspond to the data producer. Create Amazon S3 buckets than contain presigned URLS that have one-day expiration dates.

Answer

Create an AWS Direct Connect connection to the on-premises data center. Store the application keys in AWS Secrets Manager. Create Amazon S3 buckets that contain resigned URLS that have one-day expiration dates.

Question 24

A company uses AWS Glue Data Catalog to index data that is uploaded to an Amazon S3 bucket every day. The company uses a daily batch processes in an extract, transform, and load (ETL) pipeline to upload data from external sources into the S3 bucket.The company runs a daily report on the S3 data. Some days, the company runs the report before all the daily data has been uploaded to the S3 bucket. A data engineer must be able to send a message that identifies any incomplete data to an existing Amazon Simple Notification Service (Amazon SNS) topic.Which solution will meet this requirement with the LEAST operational overhead?

Accepted Answer

Create data quality checks on the source datasets that the daily reports use. Create data quality actions by using AWS Glue workflows to confirm the completeness and consistency of the datasets. Configure the data quality actions to create an event in Amazon EventBridge if a dataset is incomplete. Configure EventBridge to send the event that informs the data engineer about the incomplete datasets to the Amazon SNS topic.

Answer

Create data quality checks for the source datasets that the daily reports use. Create a new AWS managed Apache Airflow cluster. Run the data quality checks by using Airflow tasks that run data quality queries on the columns data type and the presence of null values. Configure Airflow Directed Acyclic Graphs (DAGs) to send an email notification that informs the data engineer about the incomplete datasets to the SNS topic.

Answer

Create data quality checks on the source datasets that the daily reports use. Create a new Amazon EMR cluster. Use Apache Spark SQL to create Apache Spark jobs in the EMR cluster that run data quality queries on the columns data type and the presence of null values. Orchestrate the ETL pipeline by using an AWS Step Functions workflow. Configure the workflow to send an email notification that informs the data engineer about the incomplete datasets to the SNS topic.

Answer

Create AWS Lambda functions that run data quality queries on the columns data type and the presence of null values. Orchestrate the ETL pipeline by using an AWS Step Functions workflow that runs the Lambda functions. Configure the Step Functions workflow to send an email notification that informs the data engineer about the incomplete datasets to the SNS topic.

Question 25

Two developers are working on separate application releases. The developers have created feature branches named Branch A and Branch B by using a GitHub repository's master branch as the source.The developer for Branch A deployed code to the production system. The code for Branch B will merge into a master branch in the following week's scheduled application release.Which command should the developer for Branch B run before the developer raises a pull request to the master branch?

Accepted Answer

git rebase master

Answer

git diff branchB master git commit -m <message>

Answer

git pull master

Answer

git fetch -b master

Question 26

A company needs a solution to manage costs for an existing Amazon DynamoDB table. The company also needs to control the size of the table. The solution must not disrupt any ongoing read or write operations. The company wants to use a solution that automatically deletes data from the table after 1 month.Which solution will meet these requirements with the LEAST ongoing maintenance?

Accepted Answer

Use the DynamoDB TTL feature to automatically expire data based on timestamps.

Answer

Configure a scheduled Amazon EventBridge rule to invoke an AWS Lambda function to check for data that is older than 1 month. Configure the Lambda function to delete old data.

Answer

Configure a stream on the DynamoDB table to invoke an AWS Lambda function. Configure the Lambda function to delete data in the table that is older than 1 month.

Answer

Use an AWS Lambda function to periodically scan the DynamoDB table for data that is older than 1 month. Configure the Lambda function to delete old data.

Question 27

A company stores CSV files in an Amazon S3 bucket. A data engineer needs to process the data in the CSV files and store the processed data in a new S3 bucket.The process needs to rename a column, remove specific columns, ignore the second row of each file, create a new column based on the values of the first row of the data, and filter the results by a numeric value of a column.Which solution will meet these requirements with the LEAST development effort?

Accepted Answer

Use AWS Glue DataBrew recipes to read and transform the CSV files.

Answer

Use AWS Glue Python jobs to read and transform the CSV files.

Answer

Use an AWS Glue custom crawler to read and transform the CSV files.

Answer

Use an AWS Glue workflow to build a set of jobs to crawl and transform the CSV files.

Question 28

A company uses Amazon Redshift as its data warehouse. Data encoding is applied to the existing tables of the data warehouse. A data engineer discovers that the compression encoding applied to some of the tables is not the best fit for the data.The data engineer needs to improve the data encoding for the tables that have sub-optimal encoding.Which solution will meet this requirement?

Accepted Answer

Run the ANALYZE COMPRESSION command against the identified tables. Manually update the compression encoding of columns based on the output of the command.

Answer

Run the ANALYZE command against the identified tables. Manually update the compression encoding of columns based on the output of the command.

Answer

Run the VACUUM REINDEX command against the identified tables.

Answer

Run the VACUUM RECLUSTER command against the identified tables.

Question 29

A retail company is using an Amazon Redshift cluster to support real-time inventory management. The company has deployed an ML model on a real-time endpoint in Amazon SageMaker.The company wants to make real-time inventory recommendations. The company also wants to make predictions about future inventory needs.Which solutions will meet these requirements? (Select TWO.)

Accepted Answer

Use Amazon Redshift ML to generate inventory recommendations.

Accepted Answer

Use SQL to invoke a remote SageMaker endpoint for prediction.

Answer

Use Amazon Redshift ML to schedule regular data exports for offline model training.

Answer

Use SageMaker Autopilot to create inventory management dashboards in Amazon Redshift.

Answer

Use Amazon Redshift as a file storage system to archive old inventory management reports.

Question 30

A company implements a data mesh that has a central governance account. The company needs to catalog all data in the governance account. The governance account uses AWS Lake Formation to centrally share data and grant access permissions.The company has created a new data product that includes a group of Amazon Redshift Serverless tables. A data engineer needs to share the data product with a marketing team. The marketing team must have access to only a subset of columns. The data engineer needs to share the same data product with a compliance team. The compliance team must have access to a different subset of columns than the marketing team needs access to.Which combination of steps should the data engineer take to meet these requirements? (Select TWO.)

Accepted Answer

Create views of the tables that need to be shared. Include only the required columns.

Accepted Answer

Share the Amazon Redshift data share to the Amazon Redshift Serverless workgroup in the marketing team's account.

Answer

Create an Amazon Redshift data than that includes the tables that need to be shared.

Answer

Create an Amazon Redshift managed VPC endpoint in the marketing team's account. Grant the marketing team access to the views.

Answer

Share the Amazon Redshift data share to the Lake Formation catalog in the governance account.

Question 31

A data engineer is launching an Amazon EMR duster. The data that the data engineer needs to load into the new cluster is currently in an Amazon S3 bucket. The data engineer needs to ensure that data is encrypted both at rest and in transit.The data that is in the S3 bucket is encrypted by an AWS Key Management Service (AWS KMS) key. The data engineer has an Amazon S3 path that has a Privacy Enhanced Mail (PEM) file.Which solution will meet these requirements?

Accepted Answer

Create an Amazon EMR security configuration. Specify the appropriate AWS KMS key for at-rest encryption for the S3 bucket. Specify the Amazon S3 path of the PEM file for in-transit encryption. Use the security configuration during EMR cluster creation.

Answer

Create an Amazon EMR security configuration. Specify the appropriate AWS KMS key for at-rest encryption for the S3 bucket. Create a second security configuration. Specify the Amazon S3 path of the PEM file for in-transit encryption. Create the EMR cluster, and attach both security configurations to the cluster.

Answer

Create an Amazon EMR security configuration. Specify the appropriate AWS KMS key for local disk encryption for the S3 bucket. Specify the Amazon S3 path of the PEM file for in-transit encryption. Use the security configuration during EMR cluster creation.

Answer

Create an Amazon EMR security configuration. Specify the appropriate AWS KMS key for at-rest encryption for the S3 bucket. Specify the Amazon S3 path of the PEM file for in-transit encryption. Create the EMR cluster, and attach the security configuration to the cluster.

Question 32

A company analyzes data in a data lake every quarter to perform inventory assessments. A data engineer uses AWS Glue DataBrew to detect any personally identifiable information (PII) about customers within the data. The company's privacy policy considers some custom categories of information to be PII. However, the categories are not included in standard DataBrew data quality rules.The data engineer needs to modify the current process to scan for the custom PII categories across multiple datasets within the data lake.Which solution will meet these requirements with the LEAST operational overhead?

Accepted Answer

Implement custom data quality rules in Data Brew. Apply the custom rules across datasets.

Answer

Manually review the data for custom PII categories.

Answer

Develop custom Python scripts to detect the custom PII categories. Call the scripts from DataBrew.

Answer

Implement regex patterns to extract PII information from fields during extract transform, and load (ETL) operations into the data lake.

Question 33

A marketing company uses Amazon S3 to store marketing data. The company uses versioning in some buckets. The company runs several jobs to read and load data into the buckets.To help cost-optimize its storage, the company wants to gather information about incomplete multipart uploads and outdated versions that are present in the S3 buckets.Which solution will meet these requirements with the LEAST operational effort?

Accepted Answer

Use Amazon S3 Inventory configurations reports to gather the information.

Answer

Use AWS CLI to gather the information.

Answer

Use the Amazon S3 Storage Lens dashboard to gather the information.

Answer

Use AWS usage reports for Amazon S3 to gather the information.

Question 34

A telecommunications company collects network usage data throughout each day at a rate of several thousand data points each second. The company runs an application to process the usage data in real time. The company aggregates and stores the data in an Amazon Aurora DB instance.Sudden drops in network usage usually indicate a network outage. The company must be able to identify sudden drops in network usage so the company can take immediate remedial actions.Which solution will meet this requirement with the LEAST latency?

Accepted Answer

Modify the processing application to publish the data to an Amazon Kinesis data stream. Create an Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) application to detect drops in network usage.

Answer

Create an AWS Lambda function to query Aurora for drops in network usage. Use Amazon EventBridge to automatically invoke the Lambda function every minute.

Answer

Replace the Aurora database with an Amazon DynamoDB table. Create an AWS Lambda function to query the DynamoDB table for drops in network usage every minute. Use DynamoDB Accelerator (DAX) between the processing application and DynamoDB table.

Answer

Create an AWS Lambda function within the Database Activity Streams feature of Aurora to detect drops in network usage.

Question 35

A company maintains a data warehouse in an on-premises Oracle database. The company wants to build a data lake on AWS. The company wants to load data warehouse tables into Amazon S3 and synchronize the tables with incremental data that arrives from the data warehouse every day.Each table has a column that contains monotonically increasing values. The size of each table is less than 50 GB. The data warehouse tables are refreshed every night between 1 AM and 2 AM. A business intelligence team queries the tables between 10 AM and 8 PM every day.Which solution will meet these requirements in the MOST operationally efficient way?

Accepted Answer

Use an AWS Database Migration Service (AWS DMS) full load plus CDC job to load tables that contain monotonically increasing data columns from the on-premises data warehouse to Amazon S3. Use custom logic in AWS Glue to append the daily incremental data to a full-load copy that is in Amazon S3.

Answer

Use an AWS Glue Java Database Connectivity (JDBC) connection. Configure a job bookmark for a column that contains monotonically increasing values. Write custom logic to append the daily incremental data to a full-load copy that is in Amazon S3.

Answer

Use an AWS Database Migration Service (AWS DMS) full load migration to load the data warehouse tables into Amazon S3 every day Overwrite the previous day's full-load copy every day.

Answer

Use AWS Glue to load a full copy of the data warehouse tables into Amazon S3 every day. Overwrite the previous day's full-load copy every day.

Question 36

A company is using Amazon Redshift to build a data warehouse solution. The company is loading hundreds of tiles into a tact table that is in a Redshift cluster.The company wants the data warehouse solution to achieve the greatest possible throughput. The solution must use cluster resources optimally when the company loads data into the tact table.Which solution will meet these requirements?

Accepted Answer

Use a single COPY command to load the data into the Redshift cluster.

Answer

Use multiple COPY commands to load the data into the Redshift cluster.

Answer

Use S3DistCp to load multiple files into Hadoop Distributed File System (HDFS). Use an HDFS connector to ingest the data into the Redshift cluster.

Answer

Use a number of INSERT statements equal to the number of Redshift cluster nodes. Load the data in parallel into each node.

Question 37

A company has a data warehouse that contains a table that is named Sales. The company stores the table in Amazon Redshift The table includes a column that is named city_name. The company wants to query the table to find all rows that have a city_name that starts with 'San' or 'El.'Which SQL query will meet this requirement?

Accepted Answer

Select * from Sales where city_name -, ^(San|EI) *';

Answer

Select * from Sales where city_name - '$(San|EI)';

Answer

Select * from Sales where city_name - '$(San&EI)';

Answer

Select * from Sales where city_name -, ^(San&EI)';

Question 38

A company plans to use Amazon Kinesis Data Firehose to store data in Amazon S3. The source data consists of 2 MB csv files. The company must convert the .csv files to JSON format. The company must store the files in Apache Parquet format.Which solution will meet these requirements with the LEAST development effort?

Accepted Answer

Use Kinesis Data Firehose to convert the csv files to JSON and to store the files in Parquet format.

Answer

Use Kinesis Data Firehose to convert the csv files to JSON. Use an AWS Lambda function to store the files in Parquet format.

Answer

Use Kinesis Data Firehose to invoke an AWS Lambda function that transforms the .csv files to JSON and stores the files in Parquet format.

Answer

Use Kinesis Data Firehose to invoke an AWS Lambda function that transforms the .csv files to JSON. Use Kinesis Data Firehose to store the files in Parquet format.

Question 39

A data engineer maintains a materialized view that is based on an Amazon Redshift database. The view has a column named load_date that stores the date when each row was loaded.The data engineer needs to reclaim database storage space by deleting all the rows from the materialized view.Which command will reclaim the MOST database storage space?<img alt="Amazon DEA-C01 image Question 119 121455 10292024001454000000"   width="905" height="473" src="https://examgecko.com/getfile/52c41201-f4c5-4e9a-955b-1f089f87c7ed">

Accepted Answer

Option A

Answer

Option B

Answer

Option C

Answer

Option D

Question 40

A company wants to migrate data from an Amazon RDS for PostgreSQL DB instance in the eu-east-1 Region of an AWS account named Account_A.  The company will migrate the data to an Amazon Redshift cluster in the eu-west-1 Region of an AWS account named Account_B. Which solution will give AWS Database Migration Service (AWS DMS) the ability to replicate data between two data stores?

Accepted Answer

Set up an AWS DMS replication instance in Account_B in eu-west-1.

Answer

Set up an AWS DMS replication instance in Account_B in eu-east-1.

Answer

Set up an AWS DMS replication instance in a new AWS account in eu-west-1

Answer

Set up an AWS DMS replication instance in Account_A in eu-east-1.

Amazon DEA-C01 Practice Test 3

Amazon DEA-C01 Practice Tests