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Google Updated Professional-Data-Engineer Exam Questions and Answers by huxley

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Google Professional-Data-Engineer Exam Overview :

Exam Name: Google Professional Data Engineer Exam
Exam Code: Professional-Data-Engineer Dumps
Vendor: Google Certification: Google Cloud Certified
Questions: 387 Q&A's Shared By: huxley
Question 44

You are implementing a chatbot to help an online retailer streamline their customer service. The chatbot must be able to respond to both text and voice inquiries. You are looking for a low-code or no-code option, and you want to be able to easily train the chatbot to provide answers to keywords. What should you do?

Options:

A.

Use the Speech-to-Text API to build a Python application in App Engine.

B.

Use the Speech-to-Text API to build a Python application in a Compute Engine instance.

C.

Use Dialogflow for simple queries and the Speech-to-Text API for complex queries.

D.

Use Dialogflow to implement the chatbot. defining the intents based on the most common queries collected.

Discussion
Question 45

You set up a streaming data insert into a Redis cluster via a Kafka cluster. Both clusters are running on

Compute Engine instances. You need to encrypt data at rest with encryption keys that you can create, rotate, and destroy as needed. What should you do?

Options:

A.

Create a dedicated service account, and use encryption at rest to reference your data stored in yourCompute Engine cluster instances as part of your API service calls.

B.

Create encryption keys in Cloud Key Management Service. Use those keys to encrypt your data in all of the Compute Engine cluster instances.

C.

Create encryption keys locally. Upload your encryption keys to Cloud Key Management Service. Use those keys to encrypt your data in all of the Compute Engine cluster instances.

D.

Create encryption keys in Cloud Key Management Service. Reference those keys in your API service calls when accessing the data in your Compute Engine cluster instances.

Discussion
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Question 46

You are deploying a batch pipeline in Dataflow. This pipeline reads data from Cloud Storage, transforms the data, and then writes the data into BigQuory. The security team has enabled anorganizational constraint in Google Cloud, requiring all Compute Engine instances to use only internal IP addresses and no external IP addresses. What should you do?

Options:

A.

Ensure that the firewall rules allow access to Cloud Storage and BigQuery. Use Dataflow with only internal IPs.

B.

Ensure that your workers have network tags to access Cloud Storage and BigQuery. Use Dataflow with only internal IP addresses.

C.

Create a VPC Service Controls perimeter that contains the VPC network and add Dataflow. Cloud Storage, and BigQuery as allowedservices in the perimeter. Use Dataflow with only internal IP addresses.

D.

Ensure that Private Google Access is enabled in the subnetwork. Use Dataflow with only internal IP addresses.

Discussion
Question 47

You want to analyze hundreds of thousands of social media posts daily at the lowest cost and with the fewest steps.

You have the following requirements:

You will batch-load the posts once per day and run them through the Cloud Natural Language API.

You will extract topics and sentiment from the posts.

You must store the raw posts for archiving and reprocessing.

You will create dashboards to be shared with people both inside and outside your organization.

You need to store both the data extracted from the API to perform analysis as well as the raw social media posts for historical archiving. What should you do?

Options:

A.

Store the social media posts and the data extracted from the API in BigQuery.

B.

Store the social media posts and the data extracted from the API in Cloud SQL.

C.

Store the raw social media posts in Cloud Storage, and write the data extracted from the API into BigQuery.

D.

Feed to social media posts into the API directly from the source, and write the extracted data from the API into BigQuery.

Discussion
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