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Google Professional-Data-Engineer Exam Syllabus Topics:

Section	Weight	Objectives
Operationalizing machine learning models	26%	- ML pipeline integration 1. Vertex AI pipeline deployment 2. Feature engineering and feature stores - Model deployment and monitoring 1. Online vs batch prediction 2. Model monitoring and drift detection
Building and operationalizing data processing systems	24%	- Data ingestion and integration 1. Streaming ingestion (Pub/Sub, Dataflow) 2. Batch ingestion pipelines (BigQuery, Cloud Storage) - Data processing and transformation 1. Using Dataproc, Dataflow, and BigQuery SQL 2. ETL/ELT pipeline design
Ensuring solution quality	28%	- Security and governance 1. IAM and access control in GCP 2. Data governance and compliance - Reliability and performance 1. Fault tolerance and recovery strategies 2. Monitoring pipelines and workloads
Designing data processing systems	22%	- Data architecture and storage design 1. Designing scalable and cost-effective data models 2. Choosing appropriate data storage solutions (relational, NoSQL, data warehouse) - Batch and streaming data processing design 1. Event-driven vs batch architectures 2. Latency, throughput, and consistency trade-offs

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Google Certified Professional Data Engineer Exam Sample Questions (Q384-Q389):

NEW QUESTION # 384
You are deploying an Apache Airflow directed acyclic graph (DAG) in a Cloud Composer 2 instance. You have incoming files in a Cloud Storage bucket that the DAG processes, one file at a time. The Cloud Composer instance is deployed in a subnetwork with no Internet access.
Instead of running the DAG based on a schedule, you want to run the DAG in a reactive way every time a new file is received. What should you do?

A. 1. Enable Private Google Access in the subnetwork, and set up Cloud Storage notifications to a Pub/ Sub topic.
2. Create a push subscription that points to the web server URL.
B. 1. Enable the Airflow REST API, and set up Cloud Storage notifications to trigger a Cloud Function instance.
2. Create a Private Service Connect (PSC) endpoint.
3. Write a Cloud Function that connects to the Cloud Composer cluster through the PSC endpoint.
C. 1. Enable the Airflow REST API, and set up Cloud Storage notifications to trigger a Cloud Function instance.
2. Write a Cloud Function instance to call the DAG by using the Airflow REST API and the web server URL.
3. Use VPC Serverless Access to reach the web server URL.
D. 1. Enable the Cloud Composer API, and set up Cloud Storage notifications to trigger a Cloud Function.
2. Write a Cloud Function instance to call the DAG by using the Cloud Composer API and the web server URL.
3. Use VPC Serverless Access to reach the web server URL.

Answer: B

NEW QUESTION # 385
You create a new report for your large team in Google Data Studio 360. The report uses Google BigQuery as its data source. It is company policy to ensure employees can view only the data associated with their region, so you create and populate a table for each region. You need to enforce the regional access policy to the data.
Which two actions should you take? (Choose two.)

A. Ensure each table is included in a dataset for a region.
B. Adjust the settings for each table to allow a related region-based security group view access.
C. Ensure all the tables are included in global dataset.
D. Adjust the settings for each dataset to allow a related region-based security group view access.
E. Adjust the settings for each view to allow a related region-based security group view access.

Answer: A,E

NEW QUESTION # 386
You stream order data by using a Dataflow pipeline, and write the aggregated result to Memorystore. You provisioned a Memorystore for Redis instance with Basic Tier. 4 GB capacity, which is used by 40 clients for read-only access. You are expecting the number of read-only clients to increase significantly to a few hundred and you need to be able to support the demand. You want to ensure that read and write access availability is not impacted, and any changes you make can be deployed quickly. What should you do?

A. Create a new Memorystore for Memcached instance Set a minimum of three nodes, and memory per node to 4 GB. Modify the Dataflow pipeline and all clients to use the Memcached instance Delete the old instance.
B. Create a new Memorystore for Redis instance with Standard Tier Set capacity to 5 GB and create multiple read replicas Delete the old instance.
C. Create multiple new Memorystore for Redis instances with Basic Tier (4 GB capacity) Modify the Dataflow pipeline and new clients to use all instances
D. Create a new Memorystore for Redis instance with Standard Tier Set capacity to 4 GB and read replica to No read replicas (high availability only). Delete the old instance.

Answer: B

Explanation:
The Basic Tier of Memorystore for Redis provides a standalone Redis instance that is not replicated and does not support read replicas. This means that it cannot scale horizontally to handle more read requests, and it does not provide high availability or automatic failover. If thenumber of read-only clients increases significantly, the Basic Tier instance may not be able to handle the demand and may impact the read and write access availability. Therefore, option A is not a good solution, as it would require creating multiple Basic Tier instances and modifying the Dataflow pipeline and the clients to distribute the load among them. This would increase the complexity and the management overhead of the solution.
The Standard Tier of Memorystore for Redis provides a highly available Redis instance that supports replication and read replicas. Replication ensures that the data is backed up in another zone and can fail over automatically in case of a primary node failure. Read replicas allow scaling the read throughput by adding up to five replicas to an instance and using them for read-only queries. The Standard Tier also supports in-transit encryption and maintenance windows. Therefore, option D is the best solution, as it would create a new Standard Tier instance with a higher capacity (5 GB) and multiple read replicas to handle the increased demand. The old instance can be deleted after migrating the data to the new instance.
Option B is not a good solution, as it would create a new Standard Tier instance with the same capacity (4 GB) and no read replicas. This would not improve the read throughput or the availability of the solution.
Option C is not a good solution, as it would create a new Memorystore for Memcached instance, which is a different service that uses a different protocol and data model than Redis. This would require changing the code of the Dataflow pipeline and the clients to use the Memcached protocol and data structures, which would take more time and effort than migrating to a new Redis instance. References: Redis tier capabilities | Memorystore for Redis | Google Cloud, Pricing | Memorystore for Redis | Google Cloud, What is Memorystore? | Google Cloud Blog, Working with GCP Memorystore - Simple Talk - Redgate Software

NEW QUESTION # 387
You are designing a basket abandonment system for an ecommerce company. The system will send a message to a user based on these rules:
No interaction by the user on the site for 1 hour

Has added more than $30 worth of products to the basket

Has not completed a transaction

You use Google Cloud Dataflow to process the data and decide if a message should be sent. How should you design the pipeline?

A. Use a session window with a gap time duration of 60 minutes.
B. Use a global window with a time based trigger with a delay of 60 minutes.
C. Use a fixed-time window with a duration of 60 minutes.
D. Use a sliding time window with a duration of 60 minutes.

Answer: B

NEW QUESTION # 388
Your company produces 20,000 files every hour. Each data file is formatted as a comma separated values (CSV) file that is less than 4 KB. All files must be ingested on Google Cloud Platform before they can be processed. Your company site has a 200 ms latency to Google Cloud, and your Internet connection bandwidth is limited as 50 Mbps. You currently deploy a secure FTP (SFTP) server on a virtual machine in Google Compute Engine as the data ingestion point. A local SFTP client runs on a dedicated machine to transmit the CSV files as is. The goal is to make reports with data from the previous day available to the executives by 10:00 a.m. each day. This design is barely able to keep up with the current volume, even though the bandwidth utilization is rather low.
You are told that due to seasonality, your company expects the number of files to double for the next three months. Which two actions should you take? (choose two.)

A. Assemble 1,000 files into a tape archive (TAR) file. Transmit the TAR files instead, and disassemble the CSV files in the cloud upon receiving them.
B. Create an S3-compatible storage endpoint in your network, and use Google Cloud Storage Transfer Service to transfer on-premices data to the designated storage bucket.
C. Contact your internet service provider (ISP) to increase your maximum bandwidth to at least 100 Mbps.
D. Introduce data compression for each file to increase the rate file of file transfer.
E. Redesign the data ingestion process to use gsutil tool to send the CSV files to a storage bucket in parallel.

Answer: B,E

NEW QUESTION # 389
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