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| Certification Vendor: | Google Cloud |
|---|---|
| Exam Name: | Google Cloud Professional Data Engineer Exam |
| Exam Number: | Professional-Data-Engineer |
| Certificate Validity Period: | 2 years |
| Exam Price: | USD 200 (plus tax where applicable) |
| Real Exam Qty: | 40 - 50 |
| Available Languages: | English, Japanese |
| Related Certifications: | Google Cloud Professional Cloud Architect Google Cloud Associate Cloud Engineer Google Cloud Professional Data Analyst |
| Exam Format: | Multiple choice, Multiple select |
| Exam Duration: | 120 minutes |
| Passing Score: | 700 / 1000 |
| Recommended Training: | Google Cloud Professional Data Engineer Learning Path Official Exam Guide |
| Exam Registration: | Google Cloud Certification Registration |
| Sample Questions: | Google Professional-Data-Engineer Sample Questions |
| Exam Way: | Online-proctored or onsite-proctored |
| Pre Condition: | No mandatory prerequisites; recommended 3+ years industry experience, including 1+ year designing and managing Google Cloud data solutions |
| Official Syllabus URL: | https://cloud.google.com/learn/certification/data-engineer |
>> New Google Professional-Data-Engineer Test Questions <<
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The Google Certified Professional Data Engineer Exam certification is highly respected in the industry and is recognized by many organizations as a mark of excellence in data engineering. Google Certified Professional Data Engineer Exam certification is designed to help data professionals enhance their career prospects and gain recognition for their expertise in the field. Google Certified Professional Data Engineer Exam certification is also designed to provide organizations with a reliable way to identify qualified data professionals who can help them design and manage data processing systems on the Google Cloud Platform.
NEW QUESTION # 86
When creating a new Cloud Dataproc cluster with the projects.regions.clusters.create operation, these four values are required: project, region, name, and ____.
Answer: D
Explanation:
At a minimum, you must specify four values when creating a new cluster with the projects.regions.clusters.create operation:
The project in which the cluster will be created
The region to use
The name of the cluster
The zone in which the cluster will be created
You can specify many more details beyond these minimum requirements. For example, you can also specify the number of workers, whether preemptible compute should be used, and the network settings.
NEW QUESTION # 87
Which of the following is not true about Dataflow pipelines?
Answer: B
Explanation:
Explanation
The data and transforms in a pipeline are unique to, and owned by, that pipeline. While your program can create multiple pipelines, pipelines cannot share data or transforms Reference: https://cloud.google.com/dataflow/model/pipelines
NEW QUESTION # 88
Your company has hired a new data scientist who wants to perform complicated analyses across very large datasets stored in Google Cloud Storage and in a Cassandra cluster on Google Compute Engine. The scientist primarily wants to create labelled data sets for machine learning projects, along with some visualization tasks.
She reports that her laptop is not powerful enough to perform her tasks and it is slowing her down. You want to help her perform her tasks. What should you do?
Answer: C
Explanation:
Explanation/Reference:
NEW QUESTION # 89
You are designing the architecture to process your data from Cloud Storage to BigQuery by using Dataflow. The network team provided you with the Shared VPC network and subnetwork to be used by your pipelines. You need to enable the deployment of the pipeline on the Shared VPC network. What should you do?
Answer: A
Explanation:
To use a Shared VPC network for a Dataflow pipeline, you need to specify the subnetwork parameter with the full URL of the subnetwork, and grant the service account that executes the pipeline the compute.networkUser role in the host project. This role allows the service account to use the subnetworks in the Shared VPC network. The Dataflow service agent does not need this role, as it only creates and manages the resources for the pipeline, but does not execute it. The dataflow.admin role is not related to the network access, but to the permissions to create and delete Dataflow jobs and resources. Reference:
Specify a network and subnetwork | Cloud Dataflow | Google Cloud
How to config dataflow Pipeline to use a Shared VPC?
NEW QUESTION # 90
You have a job that you want to cancel. It is a streaming pipeline, and you want to ensure that any data that is in-flight is processed and written to the output. Which of the following commands can you use on the Dataflow monitoring console to stop the pipeline job?
Answer: B
Explanation:
Using the Drain option to stop your job tells the Dataflow service to finish your job in its current state. Your job will immediately stop ingesting new data from input sources, but the Dataflow service will preserve any existing resources (such as worker instances) to finish processing and writing any buffered data in your pipeline.
Reference:
https://cloud.google.com/dataflow/pipelines/stopping-a-pipeline
NEW QUESTION # 91
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