BUY ACTUALTESTSIT GOOGLE PROFESSIONAL-DATA-ENGINEER PRACTICE QUESTIONS AND SAVE MONEY WITH FREE UPDATES

Buy ActualTestsIT Google Professional-Data-Engineer Practice Questions and Save Money With Free Updates

Buy ActualTestsIT Google Professional-Data-Engineer Practice Questions and Save Money With Free Updates

Blog Article

Tags: Professional-Data-Engineer Valid Test Questions, Professional-Data-Engineer New Real Exam, Pdf Professional-Data-Engineer Format, Professional-Data-Engineer Examcollection Dumps, Professional-Data-Engineer Exam PDF

If you buy our Professional-Data-Engineer practice engine, you can get rewords more than you can imagine. On the one hand, you can elevate your working skills after finishing learning our Professional-Data-Engineer study materials. On the other hand, you will have the chance to pass the exam and obtain the Professional-Data-Engineercertificate, which can aid your daily work and get promotion. All in all, learning never stops! It is up to your decision now. Do not regret for you past and look to the future.

To become a Google Certified Professional Data Engineer, candidates must have a strong foundation in data engineering concepts and technologies. They must also possess excellent problem-solving skills and have a deep understanding of data analysis and interpretation. Candidates can prepare for the exam by taking online courses, attending training programs, and practicing using real-world data scenarios.

>> Professional-Data-Engineer Valid Test Questions <<

Use Google Professional-Data-Engineer Questions - Complete Study Material For Google Exam

Our Google Professional-Data-Engineer training materials are compiled by professional experts. All the necessary points have been mentioned in our Google Certified Professional Data Engineer Exam Professional-Data-Engineer practice engine particularly. About some tough questions or important points, they left notes under them. Besides, our experts will concern about changes happened in Google Certified Professional Data Engineer Exam Professional-Data-Engineer study prep all the time.

The Google Certified Professional Data Engineer Exam certification exam is divided into multiple sections, each of which covers a specific area of data engineering. Professional-Data-Engineer exam is scored on a scale of 1000, with a passing score of 700 or higher. Professional-Data-Engineer Exam is computer-based and can be taken at a testing center or online. The cost of the exam is $200, and it is valid for two years.

Google Certified Professional Data Engineer Exam Sample Questions (Q166-Q171):

NEW QUESTION # 166
You have a petabyte of analytics data and need to design a storage and processing platform for it. You must be able to perform data warehouse-style analytics on the data in Google Cloud and expose the dataset as files for batch analysis tools in other cloud providers. What should you do?

  • A. Store the warm data as files in Cloud Storage, and store the active data in BigQuery. Keep this ratio as 80% warm and 20% active.
  • B. Store and process the entire dataset in BigQuery.
  • C. Store the full dataset in BigQuery, and store a compressed copy of the data in a Cloud Storage bucket.
  • D. Store and process the entire dataset in Cloud Bigtable.

Answer: C


NEW QUESTION # 167
Your company is migrating their 30-node Apache Hadoop cluster to the cloud. They want to re-use Hadoop jobs they have already created and minimize the management of the cluster as much as possible. They also want to be able to persist data beyond the life of the cluster. What should you do?

  • A. Create a Cloud Dataproc cluster that uses the Google Cloud Storage connector.
  • B. Create a Hadoop cluster on Google Compute Engine that uses Local SSD disks.
  • C. Create a Hadoop cluster on Google Compute Engine that uses persistent disks.
  • D. Create a Google Cloud Dataflow job to process the data.
  • E. Create a Google Cloud Dataproc cluster that uses persistent disks for HDFS.

Answer: A


NEW QUESTION # 168
You have uploaded 5 years of log data to Cloud Storage A user reported that some data points in the log data are outside of their expected ranges, which indicates errors You need to address this issue and be able to run the process again in the future while keeping the original data for compliance reasons. What should you do?

  • A. Create a Cloud Dataflow workflow that reads the data from Cloud Storage, checks for values outside the expected range, sets the value to an appropriate default, and writes the updated records to a new dataset in Cloud Storage
  • B. Import the data from Cloud Storage into BigQuery Create a new BigQuery table, and skip the rows with errors.
  • C. Create a Cloud Dataflow workflow that reads the data from Cloud Storage, checks for values outside the expected range, sets the value to an appropriate default, and writes the updated records to the same dataset in Cloud Storage
  • D. Create a Compute Engine instance and create a new copy of the data in Cloud Storage Skip the rows with errors

Answer: C


NEW QUESTION # 169
What are the minimum permissions needed for a service account used with Google Dataproc?

  • A. Execute to Google Cloud Storage; write to Google Cloud Logging
  • B. Write to Google Cloud Storage; read to Google Cloud Logging
  • C. Execute to Google Cloud Storage; execute to Google Cloud Logging
  • D. Read and write to Google Cloud Storage; write to Google Cloud Logging

Answer: D

Explanation:
Service accounts authenticate applications running on your virtual machine instances to other Google Cloud Platform services. For example, if you write an application that reads and writes files on Google Cloud Storage, it must first authenticate to the Google Cloud Storage API. At a minimum, service accounts used with Cloud Dataproc need permissions to read and write to Google Cloud Storage, and to write to Google Cloud Logging.
Reference: https://cloud.google.com/dataproc/docs/concepts/service-
accounts#important_notes


NEW QUESTION # 170
You operate a database that stores stock trades and an application that retrieves average stock price for a given company over an adjustable window of time. The data is stored in Cloud Bigtable where the datetime of the stock trade is the beginning of the row key. Your application has thousands of concurrent users, and you notice that performance is starting to degrade as more stocks are added. What should you do to improve the performance of your application?

  • A. Change the row key syntax in your Cloud Bigtable table to begin with a random number per second.
  • B. Change the data pipeline to use BigQuery for storing stock trades, and update your application.
  • C. Use Cloud Dataflow to write summary of each day's stock trades to an Avro file on Cloud Storage.
    Update your application to read from Cloud Storage and Cloud Bigtable to compute the responses.
  • D. Change the row key syntax in your Cloud Bigtable table to begin with the stock symbol.

Answer: A

Explanation:
Timestamp at starting of rowkey causes bottleneck issues.


NEW QUESTION # 171
......

Professional-Data-Engineer New Real Exam: https://www.actualtestsit.com/Google/Professional-Data-Engineer-exam-prep-dumps.html

Report this page