Free Access Snowflake.DEA-C01.v2026-09-04.q215 Practice Test (Page 17)

Question 76

A retail company wants to implement real-time analytics for an ecommerce platform. The company needs to collect clickstream data from the company's website and mobile apps. The company needs to store the data for analytics. Which solution will meet these requirements with the LEAST ongoing maintenance?

A.Use Amazon Data Firehose to ingest the streaming data. Deliver the processed data directly to a provisioned Amazon Redshift cluster.

B.Deploy agents on Amazon EC2 instances to collect the streaming data. Use the AWS CLI to periodically batch upload the data to an Amazon S3 bucket.

C.Use Amazon Kinesis Data Streams to collect the streaming data. Use Amazon Data Firehose to deliver the data to an Amazon S3 bucket.

D.Use an Amazon Managed Streaming for Apache Kafka (Amazon MSK) broker to collect the data.Store the data in an Amazon RDS DB instance.

Question 77

Which ones are the false statements about Materialized Views?

A.Snowflake does not allow standard DML (e.g. INSERT, UPDATE, DELETE) on ma-terialized views.

B.Snowflake does not allow users to truncate materialized views.

C.Materialized views are first-class account objects.

D.A materialized view can also be used as the data source for a subquery.

E.Materialized views can be secure views.

F.Clustering a subset of the materialized views on a table tends to be more cost-effective than clustering the table itself.

Question 78

A company receives call logs as Amazon S3 objects that contain sensitive customer information.
The company must protect the S3 objects by using encryption. The company must also use encryption keys that only specific employees can access.
Which solution will meet these requirements with the LEAST effort?

A.Use server-side encryption with customer-provided keys (SSE-C) to encrypt the objects that contain customer information. Restrict access to the keys that encrypt the objects.

B.Use an AWS CloudHSM cluster to store the encryption keys. Configure the process that writes to Amazon S3 to make calls to CloudHSM to encrypt and decrypt the objects. Deploy an IAM policy that restricts access to the CloudHSM cluster.

C.Use server-side encryption with Amazon S3 managed keys (SSE-S3) to encrypt the objects that contain customer information. Configure an IAM policy that restricts access to the Amazon S3 managed keys that encrypt the objects.

D.Use server-side encryption with AWS KMS keys (SSE-KMS) to encrypt the objects that contain customer information. Configure an IAM policy that restricts access to the KMS keys that encrypt the objects.

Question 79

A global ecommerce company occasionally receives customer data files in its Amazon S3 data lake. The company needs to automatically detect new data and mask sensitive data before making the data available to the company's analytics team.
Which solution will meet these requirements with the LEAST operational overhead?

A.Configure Amazon S3 Event Notifications to detect the new data and trigger an AWS Glue job.
Use Amazon Macie to detect and mask the sensitive data. Store the processed data in Amazon Redshift.

B.Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to detect incoming data. Use Amazon EMR workflows to detect and mask sensitive data. Store the processed data in Amazon S3.

C.Use Amazon Kinesis Data Streams to capture new data. Use Amazon Comprehend to detect and mask the sensitive data. Store the processed data in Amazon DynamoDB tables.

D.Use Amazon EventBridge to detect new data and run AWS Glue workflows. Use AWS Glue DataBrew to detect and mask the sensitive data. Store the processed data in an S3 bucket.

Question 80

Mohan, Data engineer works with ALTUSO Company, wants to programmatically check the status of the query. He needs query id to identify each query executed by Snowflake & using Snowflake Connector for Python to execute a query, how he will be able to meet this requirements. Select the best options you will suggest?

A.He can access the query ID through the sfqid attribute in the Cursor object.
1.cur = con.cursor()
2.cur.execute("SELECT * FROM snowtable")
3.print(cur.sfqid)

B.When he used the Snowflake Connector for Python to execute a query, he can access the query ID through the pyqueryid attribute in the Cursor object.

C.He needs to query history views to get the queryID as best practices.

D.Using python connector, snowflake does not support queryID retrieval for both syn-chronous & asynchronous query.

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