FEATURES OF GOOGLE PROFESSIONAL-DATA-ENGINEER DESKTOP PRACTICE EXAM SOFTWARE

Features of Google Professional-Data-Engineer Desktop Practice Exam Software

Features of Google Professional-Data-Engineer Desktop Practice Exam Software

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Google Certified Professional Data Engineer Exam Sample Questions (Q325-Q330):

NEW QUESTION # 325
What are two of the benefits of using denormalized data structures in BigQuery?

  • A. Reduces the amount of data processed, increases query speed
  • B. Increases query speed, makes queries simpler
  • C. Reduces the amount of data processed, reduces the amount of storage required
  • D. Reduces the amount of storage required, increases query speed

Answer: B

Explanation:
Denormalization increases query speed for tables with billions of rows because BigQuery's performance degrades when doing JOINs on large tables, but with a denormalized data
structure, you don't have to use JOINs, since all of the data has been combined into one table. Denormalization also makes queries simpler because you do not have to use JOIN clauses.
Denormalization increases the amount of data processed and the amount of storage required because it creates redundant data.
Reference:
https://cloud.google.com/solutions/bigquery-data-warehouse#denormalizing_data


NEW QUESTION # 326
Cloud Dataproc charges you only for what you really use with _____ billing.

  • A. month-by-month
  • B. hour-by-hour
  • C. week-by-week
  • D. minute-by-minute

Answer: D

Explanation:
Explanation
One of the advantages of Cloud Dataproc is its low cost. Dataproc charges for what you really use with minute-by-minute billing and a low, ten-minute-minimum billing period.
Reference: https://cloud.google.com/dataproc/docs/concepts/overview


NEW QUESTION # 327
You are developing an application that uses a recommendation engine on Google Cloud. Your solution
should display new videos to customers based on past views. Your solution needs to generate labels for
the entities in videos that the customer has viewed. Your design must be able to provide very fast filtering
suggestions based on data from other customer preferences on several TB of data. What should you do?

  • A. Build an application that calls the Cloud Video Intelligence API to generate labels. Store data in Cloud
    SQL, and join and filter the predicted labels to match the user's viewing history to generate
    preferences.
  • B. Build and train a complex classification model with Spark MLlib to generate labels and filter the results.
    Deploy the models using Cloud Dataproc. Call the model from your application.
  • C. Build and train a classification model with Spark MLlib to generate labels. Build and train a second
    classification model with Spark MLlib to filter results to match customer preferences. Deploy the
    models using Cloud Dataproc. Call the models from your application.
  • D. Build an application that calls the Cloud Video Intelligence API to generate labels. Store data in Cloud
    Bigtable, and filter the predicted labels to match the user's viewing history to generate preferences.

Answer: D


NEW QUESTION # 328
You want to archive data in Cloud Storage. Because some data is very sensitive, you want to use the "Trust No One" (TNO) approach to encrypt your data to prevent the cloud provider staff from decrypting your dat
a. What should you do?

  • A. Use gcloud kms keys create to create a symmetric key. Then use gcloud kms encrypt to encrypt each archival file with the key and unique additional authenticated data (AAD). Use gsutil cp to upload each encrypted file to the Cloud Storage bucket, and keep the AAD outside of Google Cloud.
  • B. Specify customer-supplied encryption key (CSEK) in the .boto configuration file. Use gsutil cp to upload each archival file to the Cloud Storage bucket. Save the CSEK in a different project that only the security team can access.
  • C. Specify customer-supplied encryption key (CSEK) in the .boto configuration file. Use gsutil cp to upload each archival file to the Cloud Storage bucket. Save the CSEK in Cloud Memorystore as permanent storage of the secret.
  • D. Use gcloud kms keys create to create a symmetric key. Then use gcloud kms encrypt to encrypt each archival file with the key. Use gsutil cp to upload each encrypted file to the Cloud Storage bucket. Manually destroy the key previously used for encryption, and rotate the key once and rotate the key once.

Answer: D


NEW QUESTION # 329
Your company is migrating its on-premises data warehousing solution to BigQuery. The existing data warehouse uses trigger-based change data capture (CDC) to apply daily updates from transactional database sources Your company wants to use BigQuery to improve its handling of CDC and to optimize the performance of the data warehouse Source system changes must be available for query m near-real time using tog-based CDC streams You need to ensure that changes in the BigQuery reporting table are available with minimal latency and reduced overhead. What should you do? Choose 2 answers

  • A. Periodically DELETE outdated records from the reporting table
    Periodically use a DML MERGE to simultaneously perform DML INSERT. UPDATE, and DELETE operations in the reporting table
  • B. Perform a DML INSERT UPDATE, or DELETE to replicate each CDC record in the reporting table m real time.
  • C. Insert each new CDC record and corresponding operation type into the reporting table in real time and use a materialized view to expose only the current version of each unique record.
  • D. Insert each new CDC record and corresponding operation type into a staging table in real time

Answer: A,C


NEW QUESTION # 330
......

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