Professional Data Engineer Certification Dumps

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How to Pass Google Professional Data Engineer exam easily? - Passcert Professional Certifications Professional Data Engineer dumps

Now there are many IT professionals in the world and the competition of IT industry is very fierce. So many IT professionals will choose to participate in the IT certification exam to improve their position in the IT industry. Professional Data Engineer exam is a very important Google's certification exam. But if you want to get a Google certification, you must pass the exam.

Share some Professional Certifications Professional Data Engineer exam questions and answers below.
You are building a model to make clothing recommendations. You know a user’s fashion preference is likely to change over time, so you build a data pipeline to stream new data back to the model as it becomes available.
How should you use this data to train the model?
A. Continuously retrain the model on just the new data.
B. Continuously retrain the model on a combination of existing data and the new data.
C. Train on the existing data while using the new data as your test set.
D. Train on the new data while using the existing data as your test set.
Answer: B

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 BigQuery, 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 BigQuery monitoring in Google Stackdriver and create an alert.
C. Import the data into BigQuery using the gcloud CLI and set max_bad_records to 0.
D. Run a Google Cloud Dataflow batch pipeline to import the data into BigQuery, and push errors to another dead-letter table for analysis.
Answer: D

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

Your company built a TensorFlow 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

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

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