Amazon-DEA-C01 Exam Questions Answers

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Page: 1 / 26
Total Questions: 130

Questions & Answers PDF

• Question 1

  

  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?

  • Use Amazon Made pattern matching as part of the ETL job.
  • Train and use the AWS Glue PySpark Filter class in the ETL job.
  • Partition tables and use the ETL job to partition the data on a unique identifier.
  • Train and use the AWS Lake Formation FindMatches transform in the ETL job.

  Reveal Answer Answer: D Next Question

• Question 2

  

  A data engineer is configuring Amazon SageMaker Studio to use AWS Glue interactive sessions toprepare 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?

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

  Reveal Answer Answer: B Next Question

• Question 3

  

  A marketing company uses Amazon S3 to store marketing datThe 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help cost-optimize its storage, the company wants to gather information about incomplete multipart uploads and outdated versions that are present in the S3 buckets.Which solution will meet these requirements with the LEAST operational effort?

  • Use AWS CLI to gather the information.
  • Use Amazon S3 Inventory configurations reports to gather the information.
  • Use the Amazon S3 Storage Lens dashboard to gather the information.
  • Use AWS usage reports for Amazon S3 to gather the information.

  Reveal Answer Answer: B Next Question

• Question 4

  

  A company uses Amazon S3 as a data lake. The company sets up a data warehouse by using a multi- node Amazon Redshift cluster. The company organizes the data files in the data lake based on the data source of each data file.The company loads all the data files into one table in the Redshift cluster by using a separate COPY command for each data file location. This approach takes a long time to load all the data files into the table. The company must increase the speed of the data ingestion. The company does not want to increase the cost of the process.Which solution will meet these requirements?

  • Use a provisioned Amazon EMR cluster to copy all the data files into one folder. Use a COPY command to load the data into Amazon Redshift.
  • Load all the data files in parallel into Amazon Aurora. Run an AWS Glue job to load the data into Amazon Redshift.
  • Use an AWS Glue job to copy all the data files into one folder. Use a COPY command to load the data into Amazon Redshift.
  • Create a manifest file that contains the data file locations. Use a COPY command to load the data into Amazon Redshift.

  Reveal Answer Answer: D Next Question

• Question 5

  

  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?

  • Define and create the calculated field in the dataset.
  • Define and create the calculated field in the analysis.
  • Define and create the calculated field in the visual.
  • Define and create the calculated field in the dashboard.

  Reveal Answer Answer: A Next Question

• Question 6

  

  A data engineer needs to join data from multiple sources to perform a one-time analysis job. The data is stored in Amazon DynamoDB, Amazon RDS, Amazon Redshift, and Amazon S3.Which solution will meet this requirement MOST cost-effectively?

  • Use an Amazon EMR provisioned cluster to read from all sources. Use Apache Spark to join the data and perform the analysis.
  • Copy the data from DynamoDB, Amazon RDS, and Amazon Redshift into Amazon S3. Run Amazon Athena queries directly on the S3 files.
  • Use Amazon Athena Federated Query to join the data from all data sources.
  • Use Redshift Spectrum to query data from DynamoDB, Amazon RDS, and Amazon S3 directly from Redshift.

  Reveal Answer Answer: C Next Question

• Question 7

  

  A security company stores IoT data that is in JSON format in an Amazon S3 bucket. The data structure can change when the company upgrades the IoT devices. The company wants to create a data catalog that includes the IoT data. The company's analytics department will use the data catalog to index the data. Which solution will meet these requirements MOST cost-effectively?

  • Create an AWS Glue Data Catalog. Configure an AWS Glue Schema Registry. Create a new AWS Glue workload to orchestrate the ingestion of the data that the analytics department will use into Amazon Redshift Serverless.
  • Create an Amazon Redshift provisioned cluster. Create an Amazon Redshift Spectrum database for the analytics department to explore the data that is in Amazon S3. Create Redshift stored procedures to load the data into Amazon Redshift.
  • Create an Amazon Athena workgroup. Explore the data that is in Amazon S3 by using Apache Spark through Athena. Provide the Athena workgroup schema and tables to the analytics department.
  • Create an AWS Glue Data Catalog. Configure an AWS Glue Schema Registry. Create AWS Lambda user defined functions (UDFs) by using the Amazon Redshift Data API. Create an AWS Step Functions job to orchestrate the ingestion of the data that the analytics department will use into Amazon Redshift Serverless.

  Reveal Answer Answer: C Next Question

• Question 8

  

  A company stores customer records in Amazon S3. The company must not delete or modify the customer record data for 7 years after each record is created. The root user also must not have the ability to delete or modify the data.A data engineer wants to use S3 Object Lock to secure the data. Which solution will meet these requirements?

  • Enable governance mode on the S3 bucket. Use a default retention period of 7 years.
  • Enable compliance mode on the S3 bucket. Use a default retention period of 7 years.
  • Place a legal hold on individual objects in the S3 bucket. Set the retention period to 7 years.
  • Set the retention period for individual objects in the S3 bucket to 7 years.

  Reveal Answer Answer: B Next Question

• Question 9

  

  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?

  • 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.
  • 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.
  • 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.
  • 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.

  Reveal Answer Answer: B Next Question

• Question 10

  

  A company is migrating its database servers from Amazon EC2 instances that run Microsoft SQL Server to Amazon RDS for Microsoft SQL Server DB instances. The company's analytics team must export large data elements every day until the migration is complete. The data elements are the result of SQL joins across multiple tables. The data must be in Apache Parquet format. The analytics team must store the data in Amazon S3.Which solution will meet these requirements in the MOST operationally efficient way?

  • Create a view in the EC2 instance-based SQL Server databases that contains the required data elements. Create an AWS Glue job that selects the data directly from the view and transfers the data in Parquet format to an S3 bucket. Schedule the AWS Glue job to run every day.
  • Schedule SQL Server Agent to run a daily SQL query that selects the desired data elements from the EC2 instance-based SQL Server databases. Configure the query to direct the output .csv objects to an S3 bucket. Create an S3 event that invokes an AWS Lambda function to transform the output format from .csv to Parquet.
  • Use a SQL query to create a view in the EC2 instance-based SQL Server databases that contains the required data elements. Create and run an AWS Glue crawler to read the view. Create an AWS Glue job that retrieves the data and transfers the data in Parquet format to an S3 bucket. Schedule the AWS Glue job to run every day.
  • Create an AWS Lambda function that queries the EC2 instance-based databases by using Java Database Connectivity (JDBC). Configure the Lambda function to retrieve the required data, transform the data into Parquet format, and transfer the data into an S3 bucket. Use Amazon EventBridge to schedule the Lambda function to run every day.

  Reveal Answer Answer: A Next Question

Page: 1 / 26
Total Questions: 130

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