Google Professional-Data-Engineer Certification Exam Dumps & Valid Professional-Data-Engineer Test Questions

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To be eligible for the Google Professional-Data-Engineer exam, candidates must have experience in data engineering, data analytics, and data warehousing. They must also have experience in designing and implementing solutions using Google Cloud Platform's data processing technologies, such as Cloud Dataflow, BigQuery, and Cloud Dataproc. Furthermore, candidates must have excellent knowledge of SQL, Python, and Java programming languages, as well as experience in data modeling and data visualization.

Google Professional-Data-Engineer Exam is one of the most prestigious and sought-after certifications in the field of data engineering. It is designed to test the knowledge, skills, and expertise of professionals in designing, building, and maintaining data processing systems on the Google Cloud Platform. Professional-Data-Engineer exam is intended for those who have experience in data engineering and are looking to validate their skills and knowledge in this field.

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Valid Professional-Data-Engineer Test Questions, Professional-Data-Engineer Paper

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Google Certified Professional Data Engineer Exam Sample Questions (Q395-Q400):

NEW QUESTION # 395
You are migrating your on-premises data warehouse to BigQuery. One of the upstream data sources resides on a MySQL database that runs in your on-premises data center with no public IP addresses. You want to ensure that the data ingestion into BigQuery is done securely and does not go through the public internet.
What should you do?

Answer: B

Explanation:
To securely ingest data from an on-premises MySQL database into BigQuery without routing through the public internet, using Datastream with Private connectivity over Cloud Interconnect is the best approach.
Here's why:
Datastream for Data Replication:
Datastream provides a managed service for data replication from various sources, including on-premises databases, to Google Cloud services like BigQuery.
Cloud Interconnect:
Cloud Interconnect establishes a private connection between your on-premises data center and Google Cloud, ensuring that data transfer occurs over a secure, private network rather than the public internet.
Private Connectivity:
Using Private connectivity with Datastream leverages the established Cloud Interconnect to securely connect your on-premises MySQL database with Google Cloud. This method ensures that the data does not traverse the public internet.
Encryption:
Using Server-only encryption ensures that data is encrypted in transit between Datastream and BigQuery, adding an extra layer of security.
Steps to Implement:
Set Up Cloud Interconnect:
Establish a Cloud Interconnect between your on-premises data center and Google Cloud to create a private connection.
Configure Datastream:
Set up Datastream to use Private connectivity as the connection method and allocate an IP address range within your VPC network.
Use Server-only encryption to ensure secure data transfer.
Create Connection Profile:
Create a connection profile in Datastream to define the connection parameters, including the use of Cloud Interconnect and Private connectivity.
Reference Links:
Datastream Documentation
Cloud Interconnect Documentation
Setting Up Private Connectivity in Datastream


NEW QUESTION # 396
You are building new real-time data warehouse for your company and will use Google BigQuery streaming inserts. There is no guarantee that data will only be sent in once but you do have a unique ID for each row of data and an event timestamp. You want to ensure that duplicates are not included while interactively querying data. Which query type should you use?

Answer: D

Explanation:
https://cloud.google.com/bigquery/docs/reference/standard-sql/analytic-function-concepts


NEW QUESTION # 397
You are implementing workflow pipeline scheduling using open source-based tools and Google Kubernetes Engine (GKE). You want to use a Google managed service to simplify and automate the task. You also want to accommodate Shared VPC networking considerations. What should you do?

Answer: B

Explanation:
Shared VPC requires that you designate a host project to which networks and subnetworks belong and a service project, which is attached to the host project. When Cloud Composer participates in a Shared VPC, the Cloud Composer environment is in the service project. Reference:
https://cloud.google.com/composer/docs/how-to/managing/configuring-shared-vpc


NEW QUESTION # 398
You are designing storage for two relational tables that are part of a 10-TB database on Google Cloud. You want to support transactions that scale horizontally. You also want to optimize data for range queries on non-key columns. What should you do?

Answer: D


NEW QUESTION # 399
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: B


NEW QUESTION # 400
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