TEST PROFESSIONAL-DATA-ENGINEER ENGINE & PROFESSIONAL-DATA-ENGINEER VCE FILE

Test Professional-Data-Engineer Engine & Professional-Data-Engineer Vce File

Test Professional-Data-Engineer Engine & Professional-Data-Engineer Vce File

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This course is normally taken by data scientists, data analysts, and business analysts who are in the field of Google Сloud. It is a good way to prepare for your final exam because it teaches you all the details including 7 modules that cover all the Professional Data Engineer exam objectives:

  • Introducing Google Cloud Platform ‘
  • Additional Resources
  • Scaling Data Analytics
  • Machine Learning
  • Data Analytics on the Cloud
  • Data Processing Architectures

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Professional-Data-Engineer Vce File | Professional-Data-Engineer Test Duration

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Exam Overview

The Professional Data Engineer certification exam is a 2-hour test consisting of the multiple-choice and multiple-select questions. The students can take it in the English or Japanese languages. To register for and schedule the exam, you must pay the fee of $200. It is possible to sit for this test in an online proctored format at a remote location. You can also take it as an on-site proctored exam at a designated testing center.

Google Certified Professional Data Engineer Exam Sample Questions (Q235-Q240):

NEW QUESTION # 235
Which of these sources can you not load data into BigQuery from?

  • A. Google Cloud Storage
  • B. File upload
  • C. Google Drive
  • D. Google Cloud SQL

Answer: D

Explanation:
You can load data into BigQuery from a file upload, Google Cloud Storage, Google Drive, or Google Cloud Bigtable. It is not possible to load data into BigQuery directly from Google Cloud SQL. One way to get data from Cloud SQL to BigQuery would be to export data from Cloud SQL to Cloud Storage and then load it from there.
Reference: https://cloud.google.com/bigquery/loading-data


NEW QUESTION # 236
You are a retailer that wants to integrate your online sales capabilities with different in-home assistants, such as Google Home. You need to interpret customer voice commands and issue an order to the backend systems. Which solutions should you choose?

  • A. Dialogflow Enterprise Edition
  • B. Cloud Speech-to-Text API
  • C. Cloud AutoML Natural Language
  • D. Cloud Natural Language API

Answer: C


NEW QUESTION # 237
Which of the following IAM roles does your Compute Engine account require to be able to run pipeline jobs?

  • A. dataflow.worker
  • B. dataflow.compute
  • C. dataflow.viewer
  • D. dataflow.developer

Answer: A

Explanation:
The dataflow.worker role provides the permissions necessary for a Compute Engine service account to execute work units for a Dataflow pipeline


NEW QUESTION # 238
Which of the following statements about Legacy SQL and Standard SQL is not true?

  • A. One difference between the two query languages is how you specify fully-qualified table names (i.e.
    table names that include their associated project name).
  • B. You need to set a query language for each dataset and the default is Standard SQL.
  • C. Standard SQL is the preferred query language for BigQuery.
  • D. If you write a query in Legacy SQL, it might generate an error if you try to run it with Standard SQL.

Answer: B

Explanation:
You do not set a query language for each dataset. It is set each time you run a query and the default query language is Legacy SQL.
Standard SQL has been the preferred query language since BigQuery 2.0 was released. In legacy SQL, to query a table with a project-qualified name, you use a colon, :, as a separator. In standard SQL, you use a period, ., instead.
Due to the differences in syntax between the two query languages (such as with project-qualified table names), if you write a query in Legacy SQL, it might generate an error if you try to run it with Standard SQL.
Reference:
https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql


NEW QUESTION # 239
Cloud Dataproc is a managed Apache Hadoop and Apache _____ service.

  • A. Ignite
  • B. Blaze
  • C. Fire
  • D. Spark

Answer: D

Explanation:
Cloud Dataproc is a managed Apache Spark and Apache Hadoop service that lets you use open source data tools for batch processing, querying, streaming, and machine learning.
Reference: https://cloud.google.com/dataproc/docs/


NEW QUESTION # 240
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