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Google Professional-Data-Engineer Exam Overview:

Certification Vendor:	Google Cloud
Exam Name:	Google Cloud Certified Professional Data Engineer
Exam Number:	Professional-Data-Engineer
Passing Score:	Not officially published (estimated ~80%)
Exam Format:	Multiple-select, Multiple-choice
Real Exam Qty:	50-60
Exam Price:	$200 USD
Available Languages:	English, Japanese
Certificate Validity Period:	2 years
Exam Duration:	120 minutes
Related Certifications:	Google Cloud Certified Professional Data Engineer
Sample Questions:	Google Professional-Data-Engineer Sample Questions
Exam Way:	Online (remote proctored) or at a testing center (Kryterion)
Pre Condition:	No mandatory prerequisites. Recommended: 3+ years of industry experience including 1+ years designing and managing solutions using Google Cloud.
Official Syllabus URL:	https://cloud.google.com/learn/certification/data-engineer

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Google Certified Professional Data Engineer Exam Sample Questions (Q420-Q425):

NEW QUESTION # 420
Does Dataflow process batch data pipelines or streaming data pipelines?

A. Only Batch Data Pipelines
B. Only Streaming Data Pipelines
C. None of the above
D. Both Batch and Streaming Data Pipelines

Answer: D

Explanation:
Explanation
Dataflow is a unified processing model, and can execute both streaming and batch data pipelines Reference: https://cloud.google.com/dataflow/

NEW QUESTION # 421
You decided to use Cloud Datastore to ingest vehicle telemetry data in real time. You want to build a storage system that will account for the long-term data growth, while keeping the costs low. You also want to create snapshots of the data periodically, so that you can make a point-in-time (PIT) recovery, or clone a copy of the data for Cloud Datastore in a different environment. You want to archive these snapshots for a long time. Which two methods can accomplish this? (Choose two.)

A. Use managed export, and then import the data into a BigQuery table created just for that export, and delete temporary export files.
B. Write an application that uses Cloud Datastore client libraries to read all the entities. Treat each entity as a BigQuery table row via BigQuery streaming insert. Assign an export timestamp for each export, and attach it as an extra column for each row. Make sure that the BigQuery table is partitioned using the export timestamp column.
C. Write an application that uses Cloud Datastore client libraries to read all the entities. Format the exported data into a JSON file. Apply compression before storing the data in Cloud Source Repositories.
D. Use managed export, and then import to Cloud Datastore in a separate project under a unique namespace reserved for that export.
E. Use managed export, and store the data in a Cloud Storage bucket using Nearline or Coldline class.

Answer: A,C

NEW QUESTION # 422
You issue a new batch job to Dataflow. The job starts successfully, processes a few elements, and then suddenly fails and shuts down. You navigate to the Dataflow monitoring interface where you find errors related to a particular DoFn in your pipeline. What is the most likely cause of the errors?

A. Exceptions in worker code
B. Insufficient permissions
C. Job validation
D. Graph or pipeline construction

Answer: A

Explanation:
While your job is running, you might encounter errors or exceptions in your worker code. These errors generally mean that the DoFns in your pipeline code have generated unhandled exceptions, which result in failed tasks in your Dataflow job.
Exceptions in user code (for example, your DoFn instances) are reported in the Dataflow monitoring interface.
Reference (Lists all answer choices and when to pick each one):
https://cloud.google.com/dataflow/docs/guides/troubleshooting-your-pipeline#Causes

NEW QUESTION # 423
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?

A. Use Apache Hive to write a Dataproc job that streams the data into BigQuery in CSV format
B. Use an Apache Beam custom connector to write a Dataflow pipeline that streams the data into BigQuery in Avro format
C. Use a standard Dataflow pipeline to store the raw data in BigQuery and then transform the format later when the data is used.
D. Write a shell script that triggers a Cloud Function that performs periodic ETL batch jobs on the new data source

Answer: B

NEW QUESTION # 424
Government regulations in your industry mandate that you have to maintain an auditable record of access
to certain types of data. Assuming that all expiring logs will be archived correctly, where should you store
data that is subject to that mandate?

A. In a BigQuery dataset that is viewable only by authorized personnel, with the Data Access log used to
provide the auditability.
B. Encrypted on Cloud Storage with user-supplied encryption keys. A separate decryption key will be
given to each authorized user.
C. In a bucket on Cloud Storage that is accessible only by an AppEngine service that collects user
information and logs the access before providing a link to the bucket.
D. In Cloud SQL, with separate database user names to each user. The Cloud SQL Admin activity logs
will be used to provide the auditability.

Answer: A

NEW QUESTION # 425
......

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