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[General] Pass Guaranteed Useful Google - Professional-Data-Engineer Free Download Pdf

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【General】 Pass Guaranteed Useful Google - Professional-Data-Engineer Free Download Pdf

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RequirementsThe certification does not have any official prerequisites. However, it is advised to have at least three years of industry experience with one or more years of expertise in designing and managing different solutions with the use of Google Cloud Platform. It is also required to review the topics of the qualifying exam before sitting for it.
Google Professional-Data-Engineer certification exam is a valuable credential for individuals seeking to advance their careers in data engineering and analytics. It validates an individual's knowledge and expertise in Google Cloud technologies and demonstrates their ability to design and implement data solutions that meet business requirements. By passing this certification exam, individuals can enhance their credibility and marketability in the competitive field of data engineering and analytics.
In order to be eligible for the exam, candidates must have at least three years of industry experience, with at least one year of experience working with Google Cloud Platform. Professional-Data-Engineer Exam consists of multiple-choice and multiple-select questions and is designed to be completed within two hours. The passing score for the exam is 70%.
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Google Certified Professional Data Engineer Exam Sample Questions (Q208-Q213):NEW QUESTION # 208
You need to move 2 PB of historical data from an on-premises storage appliance to Cloud Storage within six months, and your outbound network capacity is constrained to 20 Mb/sec. How should you migrate this data to Cloud Storage?
  • A. Use gsutil cp -J to compress the content being uploaded to Cloud Storage
  • B. Create a private URL for the historical data, and then use Storage Transfer Service to copy the data to Cloud Storage
  • C. Use Transfer Appliance to copy the data to Cloud Storage
  • D. Use trickle or ionice along with gsutil cp to limit the amount of bandwidth gsutil utilizes to less than 20 Mb/sec so it does not interfere with the production traffic
Answer: C

NEW QUESTION # 209
You have two projects where you run BigQuery jobs:
* One project runs production jobs that have strict completion time SLAs. These are high priority jobs that must have the required compute resources available when needed. These jobs generally never go below a 300 slot utilization, but occasionally spike up an additional 500 slots.
* The other project is for users to run ad-hoc analytical queries. This project generally never uses more than 200 slots at a time. You want these ad-hoc queries to be billed based on how much data users scan rather than by slot capacity.
You need to ensure that both projects have the appropriate compute resources available. What should you do?
  • A. Create a single Enterprise Edition reservation for both projects. Set a baseline of 300 slots. Enable autoscaling up to 700 slots.
  • B. Create two Enterprise Edition reservations, one for each of the projects. For the SLA project, set a baseline of 800 slots. For the ad-hoc project, enable autoscaling up to 200 slots.
  • C. Create two reservations, one for each of the projects. For the SLA project, use an Enterprise Edition with a baseline of 300 slots and enable autoscaling up to 500 slots. For the ad-hoc project, configure on-demand billing.
  • D. Create two Enterprise Edition reservations, one for each of the projects. For the SLA project, set a baseline of 300 slots and enable autoscaling up to 500 slots. For the ad-hoc project, set a reservation baseline of 0 slots and set the ignore_idle_slot3 flag to False.
Answer: C
Explanation:
To ensure that both production jobs with strict SLAs and ad-hoc queries have appropriate compute resources available while adhering to cost efficiency, setting up separate reservations and billing models for each project is the best approach. Here's why option B is the best choice:
Separate Reservations for SLA and Ad-hoc Projects:
Creating two separate reservations allows for dedicated resource management tailored to the needs of each project.
The production project requires guaranteed slots with the ability to scale up as needed, while the ad-hoc project benefits from on-demand billing based on data scanned.
Enterprise Edition Reservation for SLA Project:
Setting a baseline of 300 slots ensures that the SLA project has the minimum required resources.
Enabling autoscaling up to 500 additional slots allows the project to handle occasional spikes in workload without compromising on SLAs.
On-Demand Billing for Ad-hoc Project:
Using on-demand billing for the ad-hoc project ensures cost efficiency, as users are billed based on the amount of data scanned rather than reserved slot capacity.
This model suits the less predictable and often lower-utilization nature of ad-hoc queries.
Steps to Implement:
Set Up Enterprise Edition Reservation for SLA Project:
Create a reservation with a baseline of 300 slots.
Enable autoscaling to allow up to an additional 500 slots as needed.
Configure On-Demand Billing for Ad-hoc Project:
Ensure that the ad-hoc project is set up to use on-demand billing, which charges based on data scanned by the queries.
Monitor and Adjust:
Continuously monitor the usage and performance of both projects to ensure that the configurations meet the needs and make adjustments as necessary.
Reference:
BigQuery Slot Reservations
BigQuery On-Demand Pricing

NEW QUESTION # 210
Which of the following job types are supported by Cloud Dataproc (select 3 answers)?
  • A. YARN
  • B. Hive
  • C. Spark
  • D. Pig
Answer: B,C,D
Explanation:
Cloud Dataproc provides out-of-the box and end-to-end support for many of the most popular job types, including Spark, Spark SQL, PySpark, MapReduce, Hive, and Pig jobs.
Reference: https://cloud.google.com/datapro ... e_of_jobs_can_i_run

NEW QUESTION # 211
One of your encryption keys stored in Cloud Key Management Service (Cloud KMS) was exposed. You need to re-encrypt all of your CMEK-protected Cloud Storage data that used that key. and then delete the compromised key. You also want to reduce the risk of objects getting written without customer-managed encryption key (CMEK protection in the future. What should you do?
  • A. Create a new Cloud KMS key. Create a new Cloud Storage bucket configured to use the new key as the default CMEK key. Copy all objects from the old bucket to the new bucket without specifying a key.
  • B. Rotate the Cloud KMS key version. Continue to use the same Cloud Storage bucket.
  • C. Create a new Cloud KMS key. Set the default CMEK key on the existing Cloud Storage bucket to the new one.
  • D. Create a new Cloud KMS key. Create a new Cloud Storage bucket. Copy all objects from the old bucket to the new one bucket while specifying the new Cloud KMS key in the copy command.
Answer: D
Explanation:
To re-encrypt all of your CMEK-protected Cloud Storage data after a key has been exposed, and to ensure future writes are protected with a new key, creating a new Cloud KMS key and a new Cloud Storage bucket is the best approach. Here's why option C is the best choice:
Re-encryption of Data:
By creating a new Cloud Storage bucket and copying all objects from the old bucket to the new bucket while specifying the new Cloud KMS key, you ensure that all data is re-encrypted with the new key.
This process effectively re-encrypts the data, removing any dependency on the compromised key.
Ensuring CMEK Protection:
Creating a new bucket and setting the new CMEK as the default ensures that all future objects written to the bucket are automatically protected with the new key.
This reduces the risk of objects being written without CMEK protection.
Deletion of Compromised Key:
Once the data has been copied and re-encrypted, the old key can be safely deleted from Cloud KMS, eliminating the risk associated with the compromised key.
Steps to Implement:
Create a New Cloud KMS Key:
Create a new encryption key in Cloud KMS to replace the compromised key.
Create a New Cloud Storage Bucket:
Create a new Cloud Storage bucket and set the default CMEK to the new key.
Copy and Re-encrypt Data:
Use the gsutil tool to copy data from the old bucket to the new bucket while specifying the new CMEK key:
gsutil -o "GSUtil:gs_json_api_version=2" cp -r gs://old-bucket/* gs://new-bucket/ Delete the Old Key:
After ensuring all data is copied and re-encrypted, delete the compromised key from Cloud KMS.
Reference:
Cloud KMS Documentation
Cloud Storage Encryption
Re-encrypting Data in Cloud Storage

NEW QUESTION # 212
You are working on a sensitive project involving private user dat
  • A. Grant the consultant the Viewer role on the project.
  • B. Create a service account and allow the consultant to log on with it.
  • C. Create an anonymized sample of the data for the consultant to work with in a different project.
  • D. Grant the consultant the Cloud Dataflow Developer role on the project.
  • E. You have set up a project on Google Cloud Platform to house your work internally. An external consultant is going to assist with coding a complex transformation in a Google Cloud Dataflow pipeline for your project. How should you maintain users' privacy?
Answer: D

NEW QUESTION # 213
......
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