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Google Professional-Data-Engineer exam is a rigorous test of an individual's skills and knowledge in data engineering on Google Cloud technologies. As demand for skilled data engineering professionals continues to grow, the certification can open up many lucrative job opportunities for those looking to make their mark in the industry. Google Certified Professional Data Engineer Exam certification process requires practical experience, extensive preparation, and dedication to acquiring skills that are highly valued in today's rapidly evolving technology ecosystem.

Google Professional-Data-Engineer Certification Exam is designed to assess the skills and knowledge of candidates in various areas related to data engineering. Professional-Data-Engineer exam covers topics such as data processing architecture, data modeling, data ingestion, data transformation, and data storage. Candidates are also expected to have a strong understanding of Google Cloud technologies, including BigQuery, Cloud Storage, and Dataflow.

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Exam Topics

The syllabus of the Google Professional Data Engineer exam is divided into 4 topics, each covering specific knowledge and skills that the candidates need to develop while preparing for the test. A full outline of the exam content can be viewed on the official website. The highlights of the domains covered in the test are as follows:

Topic 1. Designing Data Processing Systems

To answer the questions related to this first topic of the certification exam, the individuals need to demonstrate their proficiency in selecting the proper storage technologies. This includes their understanding of data modeling, schema design, distributed systems, as well as tradeoffs involving throughput, latency, and transactions. Moreover, the applicants need to have the ability to map storage systems to the business needs. It also measures one’s skills in designing data pipelines, designing a data processing solution, as well as migrating data warehousing & data processing.

Google Certified Professional Data Engineer Exam Sample Questions (Q358-Q363):

NEW QUESTION # 358
A live TV show asks viewers to cast votes using their mobile phones. The event generates a large volume of data during a 3 minute period. You are in charge of the Voting restructure* and must ensure that the platform can handle the load and Hal all votes are processed. You must display partial results write voting is open. After voting doses you need to count the votes exactly once white optimizing cost. What should you do?

A. Write votes to a Pub/Sub tope and toad into both Bigtable and BigQuery via a Dataflow pipeline Query Bigtable for real-time results and BigQuery for later analysis Shutdown the Bigtable instance when voting concludes
B. Write votes to a Pub Sub tope and have Cloud Functions subscribe to it and write voles to BigQuery
C. Create a Cloud SQL for PostgreSQL database with high availability (HA) configuration and multiple read replicas
D. Create a Memorystore instance with a high availability (HA) configuration

Answer: A

NEW QUESTION # 359
Which of these rules apply when you add preemptible workers to a Dataproc cluster (select 2 answers)?

A. Preemptible workers cannot store data.
B. Preemptible workers cannot use persistent disk.
C. A Dataproc cluster cannot have only preemptible workers.
D. If a preemptible worker is reclaimed, then a replacement worker must be added manually.

Answer: A,C

Explanation:
Explanation
The following rules will apply when you use preemptible workers with a Cloud Dataproc cluster:
Processing only-Since preemptibles can be reclaimed at any time, preemptible workers do not store data.
Preemptibles added to a Cloud Dataproc cluster only function as processing nodes.
No preemptible-only clusters-To ensure clusters do not lose all workers, Cloud Dataproc cannot create preemptible-only clusters.
Persistent disk size-As a default, all preemptible workers are created with the smaller of 100GB or the primary worker boot disk size. This disk space is used for local caching of data and is not available through HDFS.
The managed group automatically re-adds workers lost due to reclamation as capacity permits.
Reference: https://cloud.google.com/dataproc/docs/concepts/preemptible-vms

NEW QUESTION # 360
You are working on a sensitive project involving private user data. 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?

A. Grant the consultant the Viewer role on the project.
B. Create an anonymized sample of the data for the consultant to work with in a different project.
C. Grant the consultant the Cloud Dataflow Developer role on the project.
D. Create a service account and allow the consultant to log on with it.

Answer: D

NEW QUESTION # 361
You work for a mid-sized enterprise that needs to move its operational system transaction data from an on-premises database to GCP. The database is about 20 TB in size. Which database should you choose?

A. Cloud SQL
B. Cloud Spanner
C. Cloud Datastore
D. Cloud Bigtable

Answer: A

NEW QUESTION # 362
You work for a financial institution that lets customers register online. As new customers register, their user data is sent to Pub/Sub before being ingested into BigQuery. For security reasons, you decide to redact your customers' Government issued Identification Number while allowing customer service representatives to view the original values when necessary. What should you do?

A. Use BigQuery column-level security. Set the table permissions so that only members of the Customer Service user group can see the SSN column.
B. Before loading the data into BigQuery, use Cloud Data Loss Prevention (DLP) to replace input values with a cryptographic format-preserving encryption token.
C. Before loading the data into BigQuery, use Cloud Data Loss Prevention (DLP) to replace input values with a cryptographic hash.
D. Use BigQuery's built-in AEAD encryption to encrypt the SSN column. Save the keys to a new table that is only viewable by permissioned users.

Answer: B

NEW QUESTION # 363
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