PROFESSIONAL-DATA-ENGINEER NEW BRAINDUMPS BOOK & PROFESSIONAL-DATA-ENGINEER LATEST BRAINDUMPS FREE

Professional-Data-Engineer New Braindumps Book & Professional-Data-Engineer Latest Braindumps Free

Professional-Data-Engineer New Braindumps Book & Professional-Data-Engineer Latest Braindumps Free

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We offer a money-back guarantee if you fail despite proper preparation and using our product (conditions are mentioned on our guarantee page). This feature gives you the peace of mind to confidently prepare for your Google Certified Professional Data Engineer Exam (Professional-Data-Engineer) certification exam. Our Google Professional-Data-Engineer exam dumps are available for instant download right after purchase, allowing you to start your Google Certified Professional Data Engineer Exam (Professional-Data-Engineer) preparation immediately.

The Google Professional-Data-Engineer exam comprises multiple-choice and scenario-based questions that test the candidate's knowledge and skills in different areas of data engineering. The test is designed to assess the candidate's ability to design and build data processing systems that meet specific business requirements. Furthermore, the exam evaluates the candidate's proficiency in data analysis, data visualization, and machine learning.

Google Professional-Data-Engineer Exam is an essential certification for professionals in the data engineering field. It demonstrates the candidate's knowledge and expertise in designing, developing, and implementing data solutions using Google Cloud Platform's technologies. Google Certified Professional Data Engineer Exam certification is recognized globally and is an excellent way to advance your career in data engineering.

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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.

Google Certified Professional Data Engineer Exam Sample Questions (Q326-Q331):

NEW QUESTION # 326
You migrated a data backend for an application that serves 10 PB of historical product data for analytics.
Only the last known state for a product, which is about 10 GB of data, needs to be served through an API to the other applications. You need to choose a cost-effective persistent storage solution that can accommodate the analytics requirements and the API performance of up to 1000 queries per second (QPS) with less than 1 second latency. What should you do?

  • A. 1. Store the historical data in Cloud SQL for analytics.
    2. In a separate table, store the last state of the product after every product change.
    3. Serve the last state data directly from Cloud SQL to the API.
  • B. 1. Store the products as a collection in Firestore with each product having a set of historical changes.
    2. Use simple and compound queries for analytics.
    3. Serve the last state data directly from Firestore to the API.
  • C. 1. Store the historical data in BigQuery for analytics.
    2. Use a materialized view to precompute the last state of a product.
    3. Serve the last state data directly from BigQuery to the API.
  • D. 1. Store the historical data in BigQuery for analytics.
    2. In a Cloud SQL table, store the last state of the product after every product change.
    3. Serve the last state data directly from Cloud SQL to the API.

Answer: C


NEW QUESTION # 327
The _________ for Cloud Bigtable makes it possible to use Cloud Bigtable in a Cloud Dataflow pipeline.

  • A. Cloud Dataflow connector
  • B. BiqQuery API
  • C. DataFlow SDK
  • D. BigQuery Data Transfer Service

Answer: A

Explanation:
The Cloud Dataflow connector for Cloud Bigtable makes it possible to use Cloud Bigtable in a Cloud Dataflow pipeline. You can use the connector for both batch and streaming operations.


NEW QUESTION # 328
Your neural network model is taking days to train. You want to increase the training speed. What can you do?

  • A. Increase the number of layers in your neural network.
  • B. Subsample your test dataset.
  • C. Increase the number of input features to your model.
  • D. Subsample your training dataset.

Answer: A

Explanation:
Reference: https://towardsdatascience.com/how-to-increase-the-accuracy-of-a-neural-network-9f5d1c6f407d


NEW QUESTION # 329
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. Contact your internet service provider (ISP) to increase your maximum bandwidth to at least 100 Mbps.
  • B. Redesign the data ingestion process to use gsutil tool to send the CSV files to a storage bucket in parallel.
  • C. 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.
  • D. Introduce data compression for each file to increase the rate file of file transfer.
  • E. 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.

Answer: A,B


NEW QUESTION # 330
You have several Spark jobs that run on a Cloud Dataproc cluster on a schedule. Some of the jobs run in sequence, and some of the jobs run concurrently. You need to automate this process. What should you do?

  • A. Create an initialization action to execute the jobs
  • B. Create a Directed Acyclic Graph in Cloud Composer
  • C. Create a Cloud Dataproc Workflow Template
  • D. Create a Bash script that uses the Cloud SDK to create a cluster, execute jobs, and then tear down the cluster

Answer: B


NEW QUESTION # 331
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