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Earning the Google Professional-Data-Engineer Certification demonstrates that an individual has the skills and knowledge required to design and maintain robust data processing systems using Google Cloud Platform services. Google Certified Professional Data Engineer Exam certification is recognized globally and is highly valued by organizations that use Google Cloud Platform for their data processing needs. With the increasing demand for data engineering professionals in the industry, earning this certification can help individuals stand out and advance their careers in this field.

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Google Certified Professional Data Engineer Exam Sample Questions (Q280-Q285):

NEW QUESTION # 280
You are using Google BigQuery as your data warehouse. Your users report that the following simple query is running very slowly, no matter when they run the query:
SELECT country, state, city FROM [myproject:mydataset.mytable] GROUP BY country You check the query plan for the query and see the following output in the Read section of Stage:1:

What is the most likely cause of the delay for this query?

Answer: C


NEW QUESTION # 281
Your analytics team wants to build a simple statistical model to determine which customers are most likely
to work with your company again, based on a few different metrics. They want to run the model on Apache
Spark, using data housed in Google Cloud Storage, and you have recommended using Google Cloud
Dataproc to execute this job. Testing has shown that this workload can run in approximately 30 minutes on
a 15-node cluster, outputting the results into Google BigQuery. The plan is to run this workload weekly.
How should you optimize the cluster for cost?

Answer: A


NEW QUESTION # 282
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?

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 # 283
An aerospace company uses a proprietary data format to store its night dat
a. You need to connect this new data source to BigQuery and stream the data into BigQuery. You want to efficiency import the data into BigQuery where consuming as few resources as possible. What should you do?

Answer: D


NEW QUESTION # 284
When running a pipeline that has a BigQuery source, on your local machine, you continue to get permission denied errors. What could be the reason for that?

Answer: C

Explanation:
When reading from a Dataflow source or writing to a Dataflow sink using DirectPipelineRunner, the Cloud Platform account that you configured with the gcloud executable will need access to the corresponding source/sink Reference: https://cloud.google.com/dataflow/java- sdk/JavaDoc/com/google/cloud/dataflow/sdk/runners/DirectPipelineRunner


NEW QUESTION # 285
......

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