Snowflake SnowPro Advanced: Data Engineer Certification - DEA-C01 FREE EXAM DUMPS QUESTIONS & ANSWERS]

Question 1

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

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Correct Answer: C Vote an answer

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Question 2

A company stores employee data in Amazon Resdshift. A table names Employee uses columns named Region ID, Department ID, and Role ID as a compound sort key.
Which queries will MOST increase the speed of query by using a compound sort key of the table?
(Choose two.)

A. Select *from Employee where Department ID=20 and Region ID='North America'; B. Select *from Employee where Region ID='North America' and Role ID=50; C. Select *from Employee where Region ID='North America'; D. Select *from Employee where Role ID=50; E. Select *from Employee where Region ID='North America' and Department ID=20;

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Correct Answer: B,E Vote an answer

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Question 3

A company has an application that uses a microservice architecture. The company hosts the application on an Amazon Elastic Kubernetes Services (Amazon EKS) cluster.
The company wants to set up a robust monitoring system for the application. The company needs to analyze the logs from the EKS cluster and the application. The company needs to correlate the cluster's logs with the application's traces to identify points of failure in the whole application request flow.
Which combination of steps will meet these requirements with the LEAST development effort?
(Choose two.)

A. Use Amazon CloudWatch to collect logs. Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to collect traces. B. Use FluentBit to collect logs. Use OpenTelemetry to collect traces. C. Use Amazon OpenSearch to correlate the logs and traces. D. Use AWS Glue to correlate the logs and traces. E. Use Amazon CloudWatch to collect logs. Use Amazon Kinesis to collect traces.

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Correct Answer: B,C Vote an answer

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Question 4

A company needs to build an extract, transform, and load (ETL) pipeline that has separate stages for batch data ingestion, transformation, and storage. The pipeline must store the transformed data in an Amazon S3 bucket. Each stage must automatically retry failures. The pipeline must provide visibility into the success or failure of individual stages.
Which solution will meet these requirements with the LEAST operational overhead?

A. Schedule Apache Airflow directed acyclic graphs (DAGs) on Amazon Manages Workflows tor Apache Airflow (Amazon MWAA) to orchestrate pipeline steps. Use Amazon Simple Queue Service (Amazon SQS) to ingest data. Use AWS Glue jobs to transform data and store the data in the S3 bucket. B. Build an Amazon EventBridge based pipeline that invokes AWS Lambda functions to perform each stage. C. Deploy AWS Step Functions workflows to orchestrate AWS Lambda functions that ingest data.
Use AWS Glue jobs to transform the data and store the data in the S3 bucket. D. Chain AWS Glue jobs that perform each stage together by using job triggers. Set the MaxRetries field to 0.

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Correct Answer: C Vote an answer

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Question 5

A data engineer needs to deploy a complex pipeline. The stages of the pipeline must be able to run a script. The data engineer must use only fully managed and serverless services in the pipeline. Which solution will meet these requirements?

A. Use Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to build and schedule the pipeline. B. Use Aws Glue DataBrew to build the pipeline. Use Amazon EventBridge to run the pipeline on a schedule. C. Deploy AWS Glue jobs and workflows. Use AWS Glue to run the jobs and workflows on a schedule. D. Deploy the script to Amazon EC2 instances. Use Amazon EventBridge to run the script on a schedule.

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Correct Answer: A Vote an answer

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Question 6

A company builds a new data pipeline to process data for business intelligence reports. Users have noticed that data is missing from the reports.
A data engineer needs to add a data quality check for columns that contain null values and for referential integrity at a stage before the data is added to storage.
Which solution will meet these requirements with the LEAST operational overhead?

A. Use Amazon SageMaker Data Wrangler and a custom Python transform to create custom rules to check for null values and referential integrity. B. Use AWS Glue ETL jobs to perform a SQL transform on the data to determine whether requested column contain null values. Use a second SQL transform to check referential integrity. C. Use Amazon SageMaker Data Wrangler to create a Data Quality and Insights report. D. Use AWS Glue ETL jobs to perform a data quality evaluation transform on the data. Use an IsComplete rule on the requested columns. Use a ReferentialItegrity rule for each join.

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Correct Answer: D Vote an answer

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Question 7

A company regularly loads data into an Amazon DynamoDB table. The company must retain the data in DynamoDB for 1 year. After 1 year, the company must archive the data for 5 years. After
5 years, the company must delete the data. Which solution will meet these requirements in the MOST operationally efficient way?

A. Include a timestamp with the data that is loaded into DynamoDB. Use an AWS Lambda function to read timestamps and move items that are 1 year old directly to Amazon S3 Glacier Deep Archive. Configure the function to delete items after 5 years. B. Enable Amazon DynamoDB Streams. Configure a TTL rule to delete items from the DynamoDB table after 1 year. Use an AWS Lambda function to consume the stream and send items to Amazon S3 Glacier Flexible Retrieval. Delete the items from S3 Glacier Flexible Retrieval after 5 years. C. Enable Amazon DynamoDB Streams. Configure a TTL rule to delete items from the DynamoDB table after 1 year. Use an AWS Lambda function to consume the stream and send items directly to Amazon S3 Glacier Deep Archive. Create an S3 Lifecycle policy to delete the items after 5 years. D. Include a timestamp with the data that is loaded into DynamoDB. Create an AWS Lambda function to read the timestamps and move items that are 1 year old to Amazon S3 Glacier Flexible Retrieval. Create an S3 Lifecycle policy to delete the items after 5 years.

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Correct Answer: C Vote an answer

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Question 8

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?

A. Set up an AWS DMS replication instance in Account_B in eu-east-1. B. Set up an AWS DMS replication instance in Account_B in eu-west-1. C. Set up an AWS DMS replication instance in a new AWS account in eu-west-1. D. Set up an AWS DMS replication instance in Account_A in eu-east-1.

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Correct Answer: A Vote an answer

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Question 9

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?

A. 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. B. 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. C. 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. D. 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.

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Correct Answer: C Vote an answer

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Question 10

You have been tasked with migrating an on-premises MySQL database to Amazon Aurora PostgreSQL using AWS Database Migration Service (DMS). The stakeholder emphasizes that the source database must remain fully operational during the migration process.
Which of the following statements about DMS is accurate with respect to this scenario?

A. AWS DMS supports both full-load and continuous replication, allowing the source MySQL database to remain operational during migration. B. AWS DMS requires the source MySQL database to be version 5.7 or higher for migrating to Amazon Aurora PostgreSQL. C. AWS DMS only supports full-load migrations, which would require downtime for the source database. D. When using DMS, the target Amazon Aurora PostgreSQL instance cannot be accessed or queried until the migration is complete. E. AWS DMS can convert the MySQL database schema directly to PostgreSQL without any manual intervention.

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Correct Answer: A Vote an answer

Question 11

A company stores customer data that contains personally identifiable information (PII) in an Amazon Redshift cluster. The company's marketing, claims, and analytics teams need to be able to access the customer data.
The marketing team should have access to obfuscated claim information but should have full access to customer contact information. The claims team should have access to customer information for each claim that the team processes. The analytics team should have access only to obfuscated PII data.
Which solution will enforce these data access requirements with the LEAST administrative overhead?

A. Create a separate Redshift cluster for each team. Load only the required data for each team.
Restrict access to clusters based on the teams. B. Move the customer data to an Amazon S3 bucket. Use AWS Lake Formation to create a data lake. Use fine-grained security capabilities to grant each team appropriate permissions to access the data. C. Create a separate Amazon Redshift database role for each team. Define masking policies that apply for each team separately. Attach appropriate masking policies to each team role. D. Create views that include required fields for each of the data requirements. Grant the teams access only to the view that each team requires.

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Correct Answer: C Vote an answer

Question 12

A data engineer has a one-time task to read data from objects that are in Apache Parquet format in an Amazon S3 bucket. The data engineer needs to query only one column of the data.
Which solution will meet these requirements with the LEAST operational overhead?

A. Run an AWS Glue crawler on the S3 objects. Use a SQL SELECT statement in Amazon Athena to query the required column. B. Prepare an AWS Glue DataBrew project to consume the S3 objects and to query the required column. C. Use S3 Select to write a SQL SELECT statement to retrieve the required column from the S3 objects. D. Configure an AWS Lambda function to load data from the S3 bucket into a pandas dataframe.
Write a SQL SELECT statement on the dataframe to query the required column.

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Correct Answer: C Vote an answer

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