Google Cloud Data Engineer Professional Professional Data Engineer Dumps in PDF

Free Google Professional Data Engineer Real Questions (page: 1)

Your company built a TensorFlow neural-network model with a large number of neurons and layers.
The model fits well for the training dat

  1. However, when tested against new data, it performs poorly.
    What method can you employ to address this?
  2. Threading
  3. Serialization
  4. Dropout Methods
  5. Dimensionality Reduction

Answer(s): C


Reference:

https://medium.com/mlreview/a-simple-deep-learning-model-for-stock-price-prediction- using-tensorflow-30505541d877



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?

  1. Continuously retrain the model on just the new data.
  2. Continuously retrain the model on a combination of existing data and the new data.
  3. Train on the existing data while using the new data as your test set.
  4. Train on the new data while using the existing data as your test set.

Answer(s): C

Explanation:

https://cloud.google.com/automl-tables/docs/prepare



You designed a database for patient records as a pilot project to cover a few hundred patients in three clinics. Your design used a single database table to represent all patients and their visits, and you used self-joins to generate reports. The server resource utilization was at 50%. Since then, the scope of the project has expanded. The database must now store 100 times more patient records. You can no longer run the reports, because they either take too long or they encounter errors with insufficient compute resources. How should you adjust the database design?

  1. Add capacity (memory and disk space) to the database server by the order of 200.
  2. Shard the tables into smaller ones based on date ranges, and only generate reports with prespecified date ranges.
  3. Normalize the master patient-record table into the patient table and the visits table, and create other necessary tables to avoid self-join.
  4. Partition the table into smaller tables, with one for each clinic. Run queries against the smaller table pairs, and use unions for consolidated reports.

Answer(s): 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?

  1. Disable caching by editing the report settings.
  2. Disable caching in BigQuery by editing table details.
  3. Refresh your browser tab showing the visualizations.
  4. Clear your browser history for the past hour then reload the tab showing the virtualizations.

Answer(s): A


Reference:

https://support.google.com/datastudio/answer/7020039?hl=en



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?

  1. Use federated data sources, and check data in the SQL query.
  2. Enable BigQuery monitoring in Google Stackdriver and create an alert.
  3. Import the data into BigQuery using the gcloud CLI and set max_bad_records to 0.
  4. Run a Google Cloud Dataflow batch pipeline to import the data into BigQuery, and push errors to another dead-letter table for analysis.

Answer(s): D



Share your comments for Google Professional Data Engineer exam with other users:

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DaveG
12/15/2023 4:50:00 PM

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S Roychowdhury
6/26/2023 5:27:00 PM

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Bella
7/22/2023 2:05:00 AM

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Scott
9/8/2023 7:19:00 AM

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donald
8/19/2023 11:05:00 AM

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8/22/2023 5:13:00 AM

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sk
5/13/2023 2:07:00 AM

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Christopher
9/5/2022 10:54:00 PM

the new versoin of this exam which i downloaded has all the latest questions from the exam. i only saw 3 new questions in the exam which was not in this dump.

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Sam
9/7/2023 6:51:00 AM

question 8 - can cloudtrail be used for storing jobs? based on aws - aws cloudtrail is used for governance, compliance and investigating api usage across all of our aws accounts. every action that is taken by a user or script is an api call so this is logged to [aws] cloudtrail. something seems incorrect here.

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Tanvi Rajput
8/14/2023 10:55:00 AM

question 13 tda - c01 answer : quick table calculation -> percentage of total , compute using table down

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PMSAGAR
9/19/2023 2:48:00 AM

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zazza
6/16/2023 10:47:00 AM

question 44 answer is user risk

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Prasana
6/23/2023 1:59:00 AM

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test user
9/24/2023 3:15:00 AM

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7/19/2023 5:34:00 AM

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Megan
4/14/2023 5:08:00 PM

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8/9/2023 6:10:00 PM

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Danny
1/15/2024 9:10:00 AM

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hanaa
10/3/2023 6:57:00 PM

is this dump still valid???

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Georgio
1/19/2024 8:15:00 AM

question 205 answer is b

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Matthew Dievendorf
5/30/2023 9:37:00 PM

question 39, should be answer b, directions stated is being sudneted from /21 to a /23. a /23 has 512 ips so 510 hosts. and can make 4 subnets out of the /21

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Adhithya
8/11/2022 12:27:00 AM

beautiful test engine software and very helpful. questions are same as in the real exam. i passed my paper.

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SuckerPumch88
4/25/2022 10:24:00 AM

the questions are exactly the same in real exam. just make sure not to answer all them correct or else they suspect you are cheating.

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soheib
7/24/2023 7:05:00 PM

question: 78 the right answer i think is d not a

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srija
8/14/2023 8:53:00 AM

very helpful

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Thembelani
5/30/2023 2:17:00 AM

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Anita
10/1/2023 4:11:00 PM

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Ben
9/9/2023 7:35:00 AM

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anonymous
9/20/2023 11:27:00 PM

hye when will post again the past year question for this h13-311_v3 part since i have to for my test tommorow…thank you very much

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Randall
9/28/2023 8:25:00 PM

on question 22, option b-once per session is also valid.

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8/28/2023 11:51:00 AM

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philly
9/18/2023 2:40:00 PM

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Beexam
9/4/2023 9:06:00 PM

correct answers are device configuration-enable the automatic installation of webview2 runtime. & policy management- prevent users from submitting feedback.

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