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The Google Certified Professional Data Engineer Exam (Professional-Data-Engineer) certification is one of the hottest career advancement credentials in the modern Google world. The Professional-Data-Engineer certification can help you to demonstrate your expertise and knowledge level. With only one badge of Professional-Data-Engineer certification, successful candidates can advance their careers and increase their earning potential. The Google Professional-Data-Engineer Certification Exam also enables you to stay updated and competitive in the market which will help you to gain more career opportunities.

Google Professional-Data-Engineer certification exam is designed to assess an individual's ability to design, build, and maintain data processing systems using Google Cloud Platform technologies. Google Certified Professional Data Engineer Exam certification exam is intended for professionals who have experience working with data technologies and are looking to enhance their skills and knowledge in cloud-based data engineering. Professional-Data-Engineer exam covers a wide range of topics such as data storage, data processing, data analysis, machine learning, and data visualization.

Google Professional-Data-Engineer Certification Exam is designed for professionals who want to demonstrate their skills in designing and building data processing systems on the Google Cloud Platform. Google Certified Professional Data Engineer Exam certification is ideal for data engineers, data analysts, and database administrators who work with big data and want to enhance their skills. Professional-Data-Engineer exam covers a broad range of topics, including data processing, data storage, data analysis, and machine learning.

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Google Certified Professional Data Engineer Exam Sample Questions (Q59-Q64):

NEW QUESTION # 59
You have a BigQuery table that ingests data directly from a Pub/Sub subscription. The ingested data is encrypted with a Google-managed encryption key. You need to meet a new organization policy that requires you to use keys from a centralized Cloud Key Management Service (Cloud KMS) project to encrypt data at rest. What should you do?

A. Use Cloud KMS encryption key with Dataflow to ingest the existing Pub/Sub subscription to the existing BigQuery table.
B. Create a new Pub/Sub topic with CMEK and use the existing BigQuery table by using Google-managed encryption key.
C. Create a new BigOuery table and Pub/Sub topic by using customer-managed encryption keys (CMEK), and migrate the data from the old Bigauery table.
D. Create a new BigOuory table by using customer-managed encryption keys (CMEK), and migrate the data from the old BigQuery table.

Answer: D

Explanation:
To use CMEK for BigQuery, you need to create a key ring and a key in Cloud KMS, and then specify the key resource name when creating or updating a BigQuery table. You cannot change the encryption type of an existing table, so you need to create a new table with CMEK and copy the data from the old table with Google-managed encryption key.
Reference:
Customer-managed Cloud KMS keys | BigQuery | Google Cloud
Creating and managing encryption keys | Cloud KMS Documentation | Google Cloud

NEW QUESTION # 60
You want to archive data in Cloud Storage. Because some data is very sensitive, you want to use the "Trust No One" (TNO) approach to encrypt your data to prevent the cloud provider staff from decrypting your dat a. What should you do?

A. Specify customer-supplied encryption key (CSEK) in the .boto configuration file. Use gsutil cp to upload each archival file to the Cloud Storage bucket. Save the CSEK in Cloud Memorystore as permanent storage of the secret.
B. Use gcloud kms keys create to create a symmetric key. Then use gcloud kms encrypt to encrypt each archival file with the key and unique additional authenticated data (AAD). Use gsutil cp to upload each encrypted file to the Cloud Storage bucket, and keep the AAD outside of Google Cloud.
C. Use gcloud kms keys create to create a symmetric key. Then use gcloud kms encrypt to encrypt each archival file with the key. Use gsutil cp to upload each encrypted file to the Cloud Storage bucket. Manually destroy the key previously used for encryption, and rotate the key once and rotate the key once.
D. Specify customer-supplied encryption key (CSEK) in the .boto configuration file. Use gsutil cp to upload each archival file to the Cloud Storage bucket. Save the CSEK in a different project that only the security team can access.

Answer: C

NEW QUESTION # 61
You are training a spam classifier. You notice that you are overfitting the training data. Which three actions can you take to resolve this problem? (Choose three.)

A. Increase the regularization parameters
B. Decrease the regularization parameters
C. Use a larger set of features
D. Reduce the number of training examples
E. Use a smaller set of features
F. Get more training examples

Answer: B,C,F

Explanation:
Explanation/Reference:

NEW QUESTION # 62
Your company is selecting a system to centralize data ingestion and delivery. You are considering messaging and data integration systems to address the requirements. The key requirements are:
The ability to seek to a particular offset in a topic, possibly back to the start of all data ever captured Support for publish/subscribe semantics on hundreds of topics Retain per-key ordering Which system should you choose?

A. Apache Kafka
B. Cloud Storage
C. Cloud Pub/Sub
D. Firebase Cloud Messaging

Answer: A

NEW QUESTION # 63
As your organization expands its usage of GCP, many teams have started to create their own projects.
Projects are further multiplied to accommodate different stages of deployments and target audiences. Each project requires unique access control configurations. The central IT team needs to have access to all projects.
Furthermore, data from Cloud Storage buckets and BigQuery datasets must be shared for use in other projects in an ad hoc way. You want to simplify access control management by minimizing the number of policies.
Which two steps should you take? (Choose two.)

A. Use Cloud Deployment Manager to automate access provision.
B. Create distinct groups for various teams, and specify groups in Cloud IAM policies.
C. Introduce resource hierarchy to leverage access control policy inheritance.
D. For each Cloud Storage bucket or BigQuery dataset, decide which projects need access. Find all the active members who have access to these projects, and create a Cloud IAM policy to grant access to all these users.
E. Only use service accounts when sharing data for Cloud Storage buckets and BigQuery datasets.

Answer: A,B

NEW QUESTION # 64
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