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Google Professional Data Engineer exam covers a wide range of topics, including the understanding of the Google Cloud Platform for storing, processing, and analyzing data, designing data processing systems, data modeling, data security, and compliance. Additionally, the exam tests the candidate's knowledge of implementing data pipelines, data transformation and processing, and machine learning models on the Google Cloud Platform. Passing Professional-Data-Engineer Exam demonstrates that the candidate has the skills and knowledge required to design and build data processing systems that meet business requirements and scale efficiently on the Google Cloud Platform.
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Google Certified Professional Data Engineer Exam Sample Questions (Q92-Q97):
NEW QUESTION # 92
Which of the following is not possible using primitive roles?
- A. Give GroupA owner access and GroupB editor access for all datasets in a project.
- B. Give a user access to view all datasets in a project, but not run queries on them.
- C. Give a user viewer access to BigQuery and owner access to Google Compute Engine instances.
- D. Give UserA owner access and UserB editor access for all datasets in a project.
Answer: B
Explanation:
Explanation
Primitive roles can be used to give owner, editor, or viewer access to a user or group, but they can't be used to separate data access permissions from job-running permissions.
Reference: https://cloud.google.com/bigquery/docs/access-control#primitive_iam_roles
NEW QUESTION # 93
Which SQL keyword can be used to reduce the number of columns processed by BigQuery?
- A. LIMIT
- B. BETWEEN
- C. SELECT
- D. WHERE
Answer: C
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.
Reference:
https://cloud.google.com/bigquery/launch-checklist#architecture_design_and_development_checklist
NEW QUESTION # 94
When a Cloud Bigtable node fails, ____ is lost.
- A. all data
- B. no data
- C. the time dimension
- D. the last transaction
Answer: B
Explanation:
Explanation
A Cloud Bigtable table is sharded into blocks of contiguous rows, called tablets, to help balance the workload of queries. Tablets are stored on Colossus, Google's file system, in SSTable format. Each tablet is associated with a specific Cloud Bigtable node.
Data is never stored in Cloud Bigtable nodes themselves; each node has pointers to a set of tablets that are stored on Colossus. As a result:
Rebalancing tablets from one node to another is very fast, because the actual data is not copied. Cloud Bigtable simply updates the pointers for each node.
Recovery from the failure of a Cloud Bigtable node is very fast, because only metadata needs to be migrated to the replacement node.
When a Cloud Bigtable node fails, no data is lost
Reference: https://cloud.google.com/bigtable/docs/overview
NEW QUESTION # 95
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. Rotate the Cloud KMS key version. Continue to use the same Cloud Storage bucket.
- B. 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.
- C. 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.
- D. Create a new Cloud KMS key. Set the default CMEK key on the existing Cloud Storage bucket to the new one.
Answer: C
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 # 96
Which of the following IAM roles does your Compute Engine account require to be able to run pipeline jobs?
- A. dataflow.viewer
- B. dataflow.worker
- C. dataflow.compute
- D. dataflow.developer
Answer: B
Explanation:
The dataflow.worker role provides the permissions necessary for a Compute Engine service account to execute work units for a Dataflow pipeline Reference: https://cloud.google.com/dataflow/access-control
NEW QUESTION # 97
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