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Google Updated Professional-Data-Engineer Exam Questions and Answers by hassan

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Google Professional-Data-Engineer Exam Overview :

Exam Name: Google Professional Data Engineer Exam
Exam Code: Professional-Data-Engineer Dumps
Vendor: Google Certification: Google Cloud Certified
Questions: 330 Q&A's Shared By: hassan
Question 56

When creating a new Cloud Dataproc cluster with the projects.regions.clusters.create operation, these four values are required: project, region, name, and ____.

Options:

A.

zone

B.

node

C.

label

D.

type

Discussion
Question 57

Which TensorFlow function can you use to configure a categorical column if you don't know all of the possible values for that column?

Options:

A.

categorical_column_with_vocabulary_list

B.

categorical_column_with_hash_bucket

C.

categorical_column_with_unknown_values

D.

sparse_column_with_keys

Discussion
Question 58

You are designing the database schema for a machine learning-based food ordering service that will predict what users want to eat. Here is some of the information you need to store:

    The user profile: What the user likes and doesn’t like to eat

    The user account information: Name, address, preferred meal times

    The order information: When orders are made, from where, to whom

The database will be used to store all the transactional data of the product. You want to optimize the data schema. Which Google Cloud Platform product should you use?

Options:

A.

BigQuery

B.

Cloud SQL

C.

Cloud Bigtable

D.

Cloud Datastore

Discussion
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Question 59

You work for a large fast food restaurant chain with over 400,000 employees. You store employee information in Google BigQuery in a Users table consisting of a FirstName field and a LastName field. A member of IT is building an application and asks you to modify the schema and data in BigQuery so the application can query a FullName field consisting of the value of the FirstName field concatenated with a space, followed by the value of the LastName field for each employee. How can you make that data available while minimizing cost?

Options:

A.

Create a view in BigQuery that concatenates the FirstName and LastName field values to produce the FullName.

B.

Add a new column called FullName to the Users table. Run an UPDATE statement that updates the FullName column for each user with the concatenation of the FirstName and LastName values.

C.

Create a Google Cloud Dataflow job that queries BigQuery for the entire Users table, concatenates the FirstName value and LastName value for each user, and loads the proper values for FirstName, LastName, and FullName into a new table in BigQuery.

D.

Use BigQuery to export the data for the table to a CSV file. Create a Google Cloud Dataproc job to process the CSV file and output a new CSV file containing the proper values for FirstName, LastName and FullName. Run a BigQuery load job to load the new CSV file into BigQuery.

Discussion
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