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Title: Get Professional-Data-Engineer Exam Real Questions - Professional-Data-Engineer Braindumps Realexamdumps.com


1
Google Professional-Data-Engineer
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data-engineer-braindumps.html
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Professional Data Engineer
A Professional Data Engineer enables data-driven
decision making by collecting, transforming, and
visualizing data. The Data Engineer designs,
builds, maintains, and troubleshoots data
processing systems with a particular emphasis on
the security, reliability, fault-tolerance,
scalability, fidelity, and efficiency of such
systems. The Data Engineer also analyzes data to
gain insight into business outcomes, builds
statistical models to support decision-making,
and creates machine learning models to automate
and simplify key business processes.
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data-engineer-braindumps.html
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The Google Cloud Certified - Professional Data
Engineer Exam Assesses Your Ability To
  • Build and maintain data structures and databases
  • check Design data processing systems
  • check Analyze data and enable machine learning
  • check Model business processes for analysis and
    optimization
  • check Design for reliability
  • check Visualize data and advocate policy
  • check Design for security and compliance

Professional Data Engineer Questions
Answers Professional Data Engineer Dumps
4
Exam Overview
  • This Exam Objectively Measures An Individuals
    Ability To Demonstrate The Critical Job Skills
    For The Role. To Earn This Certification You Must
    Pass The Professional Data Engineer Exam. The
    Format Is Multiple Choice And Multiple Select And
    Is Available In English And Japanese. The Exam
    Has No Prerequisites. This Exam Must Be Taken
    In-person At One Of Our Testing Center Locations.
  • Length 2 Hours
  • Registration Fee USD 200

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data-engineer-braindumps.html
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Prepare Google Professional-Data-Engineer
Question Answers - Professional-Data-Engineer
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Question No 1
Your company built a Tensor Flow neutral-network
model with a large number of neurons and layers.
The model fits well for the training data.
However, when tested against new data, it
performs poorly. What method can you employ to
address this? A. Threading B. Serialization C.
Dropout Methods D. Dimensionality
Reduction Answer C
Professional Data Engineer Questions
Answers Professional Data Engineer Dumps
8
Question No 2
You create an important report for your large
team in Google Data Studio 360. The report uses
Google BigQuery as its data source. You notice
that visualizations are not showing data that is
less than 1 hour old. What should you do? A.
Disable caching by editing the report
settings. B. Disable caching in BigQuery by
editing table details. C. Refresh your browser
tab showing the visualizations. D. Clear your
browser history for the past hour then reload the
tab showing the virtualizations. Answer A
Professional Data Engineer Study
Material Professional Data Engineer Braindumps
9
Question No 3
Your weather app queries a database every 15
minutes to get the current temperature. The
frontend is powered by Google App Engine and
server millions of users. How should you design
the frontend to respond to a database
failure? A. Issue a command to restart the
database servers. B. Retry the query with
exponential backoff, up to a cap of 15
minutes. C. Retry the query every second until it
comes back online to minimize staleness of
data. D. Reduce the query frequency to once every
hour until the database comes back
online. Answer B
Professional Data Engineer Study
Material Professional Data Engineer Braindumps
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Question No 4
You are creating a model to predict housing
prices. Due to budget constraints, you must run
it on a single resource-constrained virtual
machine. Which learning algorithm should you
use? A. Linear regression B. Logistic
classification C. Recurrent neural network D.
Feed forward neural network Answer A
Professional Data Engineer Study
Material Professional Data Engineer Braindumps
11
Question No 5
An external customer provides you with a daily
dump of data from their database. The data flows
into Google Cloud Storage GCS as comma-separated
values (CSV) files. You want to analyze this data
in Google Big Query, but the data could have rows
that are formatted incorrectly or corrupted. How
should you build this pipeline? A. Use federated
data sources, and check data in the SQL query. B.
Enable Big Query monitoring in Google Stack
driver and create an alert. C. Import the data
into Big Query using the cloud CLI and set
max_bad_records to 0. D. Run a Google Cloud
Dataflow batch pipeline to import the data into
Big Query, and push errors to another dead-letter
table for analysis. Answer D
Professional Data Engineer Study
Material Professional Data Engineer Braindumps
12
Professional Data Engineer Real Exam Questions -
Updated Professional Data Engineer Dumps PDF
Professional Data Engineer Questions
Answers Professional Data Engineer Dumps
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