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Understanding functional and technical aspects of Google Professional Data Engineer Exam Designing data processing systems

The following will be discussed here:

Mapping storage systems to business requirements
Data publishing and visualization (e.g., BigQuery)
System availability and fault tolerance
Data modeling
Designing data processing systems
Job automation and orchestration (e.g., Cloud Composer)
Capacity planning
Online (interactive) vs. batch predictions
Tradeoffs involving latency, throughput, transactions
Distributed systems
Hybrid cloud and edge computing
Designing data pipelines
Choice of infrastructure
Use of distributed systems
At least once, in-order, and exactly once, etc., event processing
Batch and streaming data (e.g., Cloud Dataflow, Cloud Dataproc, Apache Beam, Apache Spark and Hadoop ecosystem, Cloud Pub/Sub, Apache Kafka)
Architecture options (e.g., message brokers, message queues, middleware, service-oriented architecture, serverless functions)

Google Professional-Data-Engineer Exam is a certification offered by Google to validate the skills and expertise of data engineers. Professional-Data-Engineer exam is designed to test the ability of professionals to design, build, and maintain data processing systems that meet the needs of their organizations. It covers a wide range of topics, including data processing architecture, data modeling, data ingestion, and transformation.

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Google Certified Professional Data Engineer Exam Sample Questions (Q100-Q105):

NEW QUESTION # 100
You have a job that you want to cancel. It is a streaming pipeline, and you want to ensure that any data that is in-flight is processed and written to the output. Which of the following commands can you use on the Dataflow monitoring console to stop the pipeline job?

A. Finish
B. Stop
C. Drain
D. Cancel

Answer: C

Explanation:
Using the Drain option to stop your job tells the Dataflow service to finish your job in its current state. Your job will immediately stop ingesting new data from input sources, but the Dataflow service will preserve any existing resources (such as worker instances) to finish processing and writing any buffered data in your pipeline.

NEW QUESTION # 101
You are planning to use Google's Dataflow SDK to analyze customer data such as displayed below. Your project requirement is to extract only the customer name from the data source and then write to an output PCollection.
Tom,555 X street
Tim,553 Y street
Sam, 111 Z street
Which operation is best suited for the above data processing requirement?

A. Sink API
B. Data extraction
C. Source API
D. ParDo

Answer: D

Explanation:
In Google Cloud dataflow SDK, you can use the ParDo to extract only a customer name of each element in your PCollection.

NEW QUESTION # 102
You create an important report for your large team in Google Data Studio 360. The report uses Google BigQuery as its data source. You notice that visualizations are not showing data that is less than 1 hour old. What should you do?

A. Disable caching by editing the report settings.
B. Clear your browser history for the past hour then reload the tab showing the virtualizations.
C. Refresh your browser tab showing the visualizations.
D. Disable caching in BigQuery by editing table details.

Answer: A

Explanation:
https://support.google.com/datastudio/answer/7020039?hl=en

NEW QUESTION # 103
Your team is responsible for developing and maintaining ETLs in your company. One of your Dataflow jobs is failing because of some errors in the input data, and you need to improve reliability of the pipeline (incl. being able to reprocess all failing data).
What should you do?

A. Add a try... catch block to your DoFn that transforms the data, use a sideOutput to create a PCollection that can be stored to PubSub later.
B. Add a filtering step to skip these types of errors in the future, extract erroneous rows from logs.
C. Add a try... catch block to your DoFn that transforms the data, extract erroneous rows from logs.
D. Add a try... catch block to your DoFn that transforms the data, write erroneous rows to PubSub directly from the DoFn.

Answer: D

NEW QUESTION # 104
You need to connect multiple applications with dynamic public IP addresses to a Cloud SQL instance. You configured users with strong passwords and enforced the SSL connection to your Cloud SOL instance. You want to use Cloud SQL public IP and ensure that you have secured connections. What should you do?

A. Add all application networks to Authorized Network and regularly update them.
B. Add CIDR 0.0.0.0/0 network to Authorized Network. Use Cloud SOL Auth proxy on all applications.
C. Leave the Authorized Network empty. Use Cloud SQL Auth proxy on all applications.
D. Add CIDR 0.0.0.0/0 network to Authorized Network. Use Identity and Access Management (1AM) to add users.

Answer: C

Explanation:
To securely connect multiple applications with dynamic public IP addresses to a Cloud SQL instance using public IP, the Cloud SQL Auth proxy is the best solution. This proxy provides secure, authorized connections to Cloud SQL instances without the need to configure authorized networks or deal with IP whitelisting complexities.
Cloud SQL Auth Proxy:
The Cloud SQL Auth proxy provides secure, encrypted connections to Cloud SQL.
It uses IAM permissions and SSL to authenticate and encrypt the connection, ensuring data security in transit.
By using the proxy, you avoid the need to constantly update authorized networks as the proxy handles dynamic IP addresses seamlessly.
Authorized Network Configuration:
Leaving the authorized network empty means no IP addresses are explicitly whitelisted, relying solely on the Auth proxy for secure connections.
This approach simplifies network management and enhances security by not exposing the Cloud SQL instance to public IP ranges.
Dynamic IP Handling:
Applications with dynamic IP addresses can securely connect through the proxy without the need to modify authorized networks.
The proxy authenticates connections using IAM, making it ideal for environments where application IPs change frequently.
Google Data Engineer Reference:
Using Cloud SQL Auth Proxy
Cloud SQL Security Overview
Setting up the Cloud SQL Auth Proxy
By using the Cloud SQL Auth proxy, you ensure secure, authorized connections for applications with dynamic public IPs without the need for complex network configurations.

NEW QUESTION # 105
......

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