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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q208-Q213):

NEW QUESTION # 208
A company stores a 100 MB dataset in an Amazon S3 bucket as an Apache Parquet file. A data engineer needs to profile the data before performing data preparation steps on the data. Which solution will meet this requirement in the MOST operationally efficient way?

A. Stream the data into Amazon Managed Service for Apache Flink for SQL queries. Use the Apache Flink dashboard to profile the data.
B. Create a profile job on the dataset in AWS Glue DataBrew. Review the profile job results.
C. Load the data into an Amazon QuickSight dataset. Build a topic to profile the data with questions.
D. Ingest the data into Amazon Redshift Spectrum. Use SQL queries to profile the data.

Answer: B

Explanation:
AWS Glue DataBrew provides built-in data profiling specifically for exploring dataset structure, data types, distributions, missing values, and anomalies before preparation. For a 100 MB Parquet file in Amazon S3, creating a profile job is the most operationally efficient approach because it requires minimal setup and no custom infrastructure or query framework.

NEW QUESTION # 209
A retail company stores customer data in an Amazon S3 bucket. Some of the customer data contains personally identifiable information (PII) about customers. The company must not share PII data with business partners.
A data engineer must determine whether a dataset contains PII before making objects in the dataset available to business partners.
Which solution will meet this requirement with the LEAST manual intervention?

A. Create a table in AWS Glue Data Catalog. Write custom SQL queries to identify PII in the table.Use Amazon Athena to run the queries.
B. Create an AWS Lambda function to identify PII in S3 objects. Schedule the function to run periodically.
C. Configure AWS CloudTrail to monitor S3 PUT operations. Inspect the CloudTrail trails to identify operations that save PII.
D. Configure the S3 bucket and S3 objects to allow access to Amazon Macie. Use automated sensitive data discovery in Macie.

Answer: D

Explanation:
Amazon Macie is a fully managed data security service that automatically discovers, classifies, and protects sensitive data such as personally identifiable information (PII) in Amazon S3.
Macie's automated sensitive data discovery feature can scan S3 objects for PII without requiring manual intervention, making it the most efficient and automated solution for identifying sensitive data before sharing it with business partners.
CloudTrail is useful for monitoring API calls but is not designed to inspect the contents of S3 objects for PII. This would require manual effort to inspect the data saved in S3, which is inefficient.
While Lambda could be used to scan for PII, it would require custom code to identify sensitive data. This approach increases manual effort for development and maintenance compared to using a fully managed service like Macie.
Writing custom SQL queries to identify PII is a manual process and requires the creation and management of Glue tables and Athena queries. This approach adds complexity and manual intervention compared to the automated capabilities of Macie.

NEW QUESTION # 210
A company has a data pipeline that uses an Amazon RDS instance, AWS Glue jobs, and an Amazon S3 bucket. The RDS instance and AWS Glue jobs run in a private subnet of a VPC and in the same security group.
A user made a change to the security group that prevents the AWS Glue jobs from connecting to the RDS instance. After the change, the security group contains a single rule that allows inbound SSH traffic from a specific IP address.
The company must resolve the connectivity issue.
Which solution will meet this requirement?

A. Add an inbound rule that allows all TCP traffic on all TCP ports. Set the DNS name of the RDS instance as the source.
B. Add an inbound rule that allows all TCP traffic on all UDP ports. Set the private IP address of the RDS instance as the source.
C. Replace the source of the existing SSH rule with the private IP address of the RDS instance.Create an outbound rule with the same source, destination, and protocol as the inbound SSH rule.
D. Add an inbound rule that allows all TCP traffic on all TCP ports. Set the security group as the source.

Answer: D

Explanation:
Since both the RDS instance and the Glue jobs share the same security group, allowing that security group as the source for inbound TCP traffic (on all ports) immediately restores connectivity from the Glue-attached ENIs to the database. This single rule change requires no additional infrastructure and incurs no extra maintenance.

NEW QUESTION # 211
A data engineer must build an extract, transform, and load (ETL) pipeline to process and load data from 10 source systems into 10 tables that are in an Amazon Redshift database. All the source systems generate .csv, JSON, or Apache Parquet files every 15 minutes. The source systems all deliver files into one Amazon S3 bucket. The file sizes range from 10 MB to 20 GB.
The ETL pipeline must function correctly despite changes to the data schema.
Which data pipeline solutions will meet these requirements? (Choose two.)

A. Use an Amazon EventBridge rule to run an AWS Glue job every 15 minutes. Configure the AWS Glue job to process and load the data into the Amazon Redshift tables.
B. Configure an AWS Lambda function to invoke an AWS Glue crawler when a file is loaded into the S3 bucket. Configure an AWS Glue job to process and load the data into the Amazon Redshift tables. Create a second Lambda function to run the AWS Glue job. Create an Amazon EventBridge rule to invoke the second Lambda function when the AWS Glue crawler finishes running successfully.
C. Configure an AWS Lambda function to invoke an AWS Glue job when a file is loaded into the S3 bucket. Configure the AWS Glue job to read the files from the S3 bucket into an Apache Spark DataFrame. Configure the AWS Glue job to also put smaller partitions of the DataFrame into an Amazon Kinesis Data Firehose delivery stream. Configure the delivery stream to load data into the Amazon Redshift tables.
D. Configure an AWS Lambda function to invoke an AWS Glue workflow when a file is loaded into the S3 bucket. Configure the AWS Glue workflow to have an on-demand trigger that runs an AWS Glue crawler and then runs an AWS Glue job when the crawler finishes running successfully. Configure the AWS Glue job to process and load the data into the Amazon Redshift tables.
E. Use an Amazon EventBridge rule to invoke an AWS Glue workflow job every 15 minutes.
Configure the AWS Glue workflow to have an on-demand trigger that runs an AWS Glue crawler and then runs an AWS Glue job when the crawler finishes running successfully. Configure the AWS Glue job to process and load the data into the Amazon Redshift tables.

Answer: D,E

NEW QUESTION # 212
An online retail company stores Application Load Balancer (ALB) access logs in an Amazon S3 bucket. The company wants to use Amazon Athena to query the logs to analyze traffic patterns.
A data engineer creates an unpartitioned table in Athena. As the amount of the data gradually increases, the response time for queries also increases. The data engineer wants to improve the query performance in Athena.
Which solution will meet these requirements with the LEAST operational effort?

A. Use Apache Hive to create bucketed tables. Use an AWS Lambda function to transform all ALB access logs.
B. Create an AWS Lambda function to transform all ALB access logs. Save the results to Amazon S3 in Apache Parquet format. Partition the metadata. Use Athena to query the transformed data.
C. Create an AWS Glue job that determines the schema of all ALB access logs and writes the partition metadata to AWS Glue Data Catalog.
D. Create an AWS Glue crawler that includes a classifier that determines the schema of all ALB access logs and writes the partition metadata to AWS Glue Data Catalog.

Answer: D

Explanation:
An AWS Glue crawler can automatically determine the schema of the logs, infer partitions, and update the Glue Data Catalog. Crawlers can be scheduled to run at intervals, minimizing manual intervention.

NEW QUESTION # 213
......

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Achieve your goals with DEA-C01 actual dumps & Snowflake DEA-C01 exam pdf

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DEA-C01 Test Valid | DEA-C01 Latest Exam

Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q208-Q213):

Free PDF Quiz 2026 High-quality Snowflake DEA-C01: SnowPro Advanced: Data Engineer Certification Exam Reliable Exam Pass4sure

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