QUIZ PROFESSIONAL-DATA-ENGINEER - GOOGLE CERTIFIED PROFESSIONAL DATA ENGINEER EXAM–VALID RELIABLE TEST PREPARATION

Quiz Professional-Data-Engineer - Google Certified Professional Data Engineer Exam–Valid Reliable Test Preparation

Quiz Professional-Data-Engineer - Google Certified Professional Data Engineer Exam–Valid Reliable Test Preparation

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Training Courses Recommended for the Exam Preparation

Training courses are meant to help candidates to learn about the Google exam syllabus and prepare well. It has hands-on labs and expert support that will allow you to get in-depth knowledge of each domain covered in the test. So, these are some of the best training courses offered by Google for the Professional Data Engineer certification exam.

Google Certified Professional Data Engineer Exam Sample Questions (Q84-Q89):

NEW QUESTION # 84
You need to choose a database for a new project that has the following requirements:
* Fully managed
* Able to automatically scale up
* Transactionally consistent
* Able to scale up to 6 TB
* Able to be queried using SQL
Which database do you choose?

  • A. Cloud Datastore
  • B. Cloud Bigtable
  • C. Cloud Spanner
  • D. Cloud SQL

Answer: C

Explanation:
https://cloud.google.com/products/databases


NEW QUESTION # 85
Your company is performing data preprocessing for a learning algorithm in Google Cloud Dataflow.
Numerous data logs are being are being generated during this step, and the team wants to analyze them.
Due to the dynamic nature of the campaign, the data is growing exponentially every hour. The data scientists have written the following code to read the data for a new key features in the logs.
BigQueryIO.Read
.named("ReadLogData")
.from("clouddataflow-readonly:samples.log_data")
You want to improve the performance of this data read. What should you do?

  • A. Call a transform that returns TableRow objects, where each element in the PCollexction represents a single row in the table.
  • B. Specify the TableReference object in the code.
  • C. Use of both the Google BigQuery TableSchema and TableFieldSchema classes.
  • D. Use .fromQuery operation to read specific fields from the table.

Answer: A


NEW QUESTION # 86
Which of these is NOT a way to customize the software on Dataproc cluster instances?

  • A. Set initialization actions
  • B. Modify configuration files using cluster properties
  • C. Log into the master node and make changes from there
  • D. Configure the cluster using Cloud Deployment Manager

Answer: D

Explanation:
You can access the master node of the cluster by clicking the SSH button next to it in the Cloud Console.
You can easily use the --properties option of the dataproc command in the Google Cloud SDK to modify many common configuration files when creating a cluster.
When creating a Cloud Dataproc cluster, you can specify initialization actions in executables and/or scripts that Cloud Dataproc will run on all nodes in your Cloud Dataproc cluster immediately after the cluster is set up. [https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/init-actions] Reference: https://cloud.google.com/dataproc/docs/concepts/configuring-clusters/cluster-properties


NEW QUESTION # 87
Each analytics team in your organization is running BigQuery jobs in their own projects. You want to enable each team to monitor slot usage within their projects. What should you do?

  • A. Create a Stackdriver Monitoring dashboard based on the BigQuery metric slots/allocated_for_project
  • B. Create an aggregated log export at the organization level, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Stackdriver Monitoring dashboard based on the custom metric
  • C. Create a log export for each project, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Stackdriver Monitoring dashboard based on the custom metric
  • D. Create a Stackdriver Monitoring dashboard based on the BigQuery metric query/scanned_bytes

Answer: B


NEW QUESTION # 88
The Development and External teams nave the project viewer Identity and Access Management (1AM) role m a folder named Visualization. You want the Development Team to be able to read data from both Cloud Storage and BigQuery, but the External Team should only be able to read data from BigQuery. What should you do?

  • A. Create a VPC Service Controls perimeter containing both protects and BigQuery as a restricted API Add the External Team users to the perimeter s Access Level
  • B. Create Virtual Private Cloud (VPC) firewall rules on the acme-raw-data protect that deny all Ingress traffic from the External Team CIDR range
  • C. Remove Cloud Storage IAM permissions to the External Team on the acme-raw-data project
  • D. Create a VPC Service Controls perimeter containing both protects and Cloud Storage as a restricted API. Add the Development Team users to the perimeter's Access Level

Answer: A


NEW QUESTION # 89
......

No doubt the Google Professional-Data-Engineer certification is a valuable credential that offers countless advantages to Professional-Data-Engineer exam holders. Beginners and experienced professionals can validate their skills and knowledge level with the Google Certified Professional Data Engineer Exam Professional-Data-Engineer Exam and earn solid proof of their proven skills.

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