Google Professional-Data-Engineer Latest Dumps | Professional-Data-Engineer Valid Dumps Ppt

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Google Professional-Data-Engineer Exam is one of the most sought-after certifications in the world of tech. Professional-Data-Engineer exam is designed for data engineers who work with Google Cloud technologies and want to demonstrate their expertise in designing and building scalable data processing systems on the Google Cloud platform. Successful completion of the exam results in a Google Certified Professional Data Engineer certification, which is highly valued in the industry.

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Google Professional-Data-Engineer Certification is a globally recognized certification that validates the skills and expertise of professionals in the field of data engineering. Google Certified Professional Data Engineer Exam certification is offered by Google and is designed to test the proficiency of individuals in designing, building, and managing data processing systems, as well as analyzing and interpreting data. Google Certified Professional Data Engineer Exam certification is aimed at individuals who are looking to enhance their career prospects in the field of data engineering.

Google Certified Professional Data Engineer Exam Sample Questions (Q398-Q403):

NEW QUESTION # 398
You work for a shipping company that uses handheld scanners to read shipping labels. Your company has strict data privacy standards that require scanners to only transmit recipients' personally identifiable information (PII) to analytics systems, which violates user privacy rules. You want to quickly build a scalable solution using cloud-native managed services to prevent exposure of PII to the analytics systems. What should you do?

A. Create an authorized view in BigQuery to restrict access to tables with sensitive data.
B. Build a Cloud Function that reads the topics and makes a call to the Cloud Data Loss Prevention API.
Use the tagging and confidence levels to either pass or quarantine the data in a bucket for review.
C. Use Stackdriver logging to analyze the data passed through the total pipeline to identify transactions that may contain sensitive information.
D. Install a third-party data validation tool on Compute Engine virtual machines to check the incoming data for sensitive information.

Answer: A

NEW QUESTION # 399
You are designing a messaging system by using Pub/Sub to process clickstream data with an event-driven consumer app that relies on a push subscription. You need to configure the messaging system that is reliable enough to handle temporary downtime of the consumer app. You also need the messaging system to store the input messages that cannot be consumed by the subscriber. The system needs to retry failed messages gradually, avoiding overloading the consumer app, and store the failed messages after a maximum of 10 retries in a topic. How should you configure the Pub/Sub subscription?

A. Use exponential backoff as the subscription retry policy, and configure dead lettering to a different topic with maximum delivery attempts set to 10.
B. Use immediate redelivery as the subscription retry policy, and configure dead lettering to a different topic with maximum delivery attempts set to 10.
C. Increase the acknowledgement deadline to 10 minutes.
D. Use exponential backoff as the subscription retry policy, and configure dead lettering to the same source topic with maximum delivery attempts set to 10.

Answer: A

NEW QUESTION # 400
Which SQL keyword can be used to reduce the number of columns processed by BigQuery?

A. BETWEEN
B. SELECT
C. LIMIT
D. WHERE

Answer: B

Explanation:
SELECT allows you to query specific columns rather than the whole table.
LIMIT, BETWEEN, and WHERE clauses will not reduce the number of columns processed by
BigQuery.

NEW QUESTION # 401
You work on a regression problem in a natural language processing domain, and you have 100M labeled exmaples in your dataset. You have randomly shuffled your data and split your dataset into train and test samples (in a 90/10 ratio). After you trained the neural network and evaluated your model on a test set, you discover that the root-mean-squared error (RMSE) of your model is twice as high on the train set as on the test set. How should you improve the performance of your model?

A. Increase the complexity of your model by, e.g., introducing an additional layer or increase sizing the size of vocabularies or n-grams used.
B. Increase the share of the test sample in the train-test split.
C. Try out regularization techniques (e.g., dropout of batch normalization) to avoid overfitting.
D. Try to collect more data and increase the size of your dataset.

Answer: C

NEW QUESTION # 402
What are two of the characteristics of using online prediction rather than batch prediction?

A. It is optimized to handle a high volume of data instances in a job and to run more complex models.
B. It is optimized to minimize the latency of serving predictions.
C. Predictions are returned in the response message.
D. Predictions are written to output files in a Cloud Storage location that you specify.

Answer: B,C

Explanation:
Explanation
Online prediction
Optimized to minimize the latency of serving predictions.
Predictions returned in the response message.
Batch prediction
Optimized to handle a high volume of instances in a job and to run more complex models.
Predictions written to output files in a Cloud Storage location that you specify.
Reference:
https://cloud.google.com/ml-engine/docs/prediction-overview#online_prediction_versus_batch_prediction

NEW QUESTION # 403
......

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