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PROFESSIONAL-DATA-ENGINEER Questions and Answers

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Google PROFESSIONAL-DATA-ENGINEER dumps - 100% Pass Guarantee!

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Vendor: Google

Certifications: Google Certifications

Exam Name: Professional Data Engineer on Google Cloud Platform

Exam Code: PROFESSIONAL-DATA-ENGINEER

Total Questions: 269 Q&As

Last Updated: Sep 18, 2023

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Same Questions from the Latest Real Exam

PROFESSIONAL-DATA-ENGINEER Online Practice Questions and Answers

Questions 1

How would you query specific partitions in a BigQuery table?

A. Use the DAY column in the WHERE clause

B. Use the EXTRACT(DAY) clause

C. Use the __PARTITIONTIME pseudo-column in the WHERE clause

D. Use DATE BETWEEN in the WHERE clause

Show Answer
Questions 2

You launched a new gaming app almost three years ago. You have been uploading log files from the previous day to a separate Google BigQuery table with the table name format LOGS_yyyymmdd. You have been using table wildcard functions to generate daily and monthly reports for all time ranges. Recently, you discovered that some queries that cover long date ranges are exceeding the limit of 1,000 tables and failing. How can you resolve this issue?

A. Convert all daily log tables into date-partitioned tables

B. Convert the sharded tables into a single partitioned table

C. Enable query caching so you can cache data from previous months

D. Create separate views to cover each month, and query from these views

Show Answer
Questions 3

You need to compose visualizations for operations teams with the following requirements:

1.

The report must include telemetry data from all 50,000 installations for the most resent 6 weeks (sampling once every minute).

2.

The report must not be more than 3 hours delayed from live data.

3.

The actionable report should only show suboptimal links.

4.

Most suboptimal links should be sorted to the top.

5.

Suboptimal links can be grouped and filtered by regional geography.

6.

User response time to load the report must be <5 seconds. Which approach meets the requirements?

A. Load the data into Google Sheets, use formulas to calculate a metric, and use filters/sorting to show only suboptimal links in a table.

B. Load the data into Google BigQuery tables, write Google Apps Script that queries the data, calculates the metric, and shows only suboptimal rows in a table in Google Sheets.

C. Load the data into Google Cloud Datastore tables, write a Google App Engine Application that queries all rows, applies a function to derive the metric, and then renders results in a table using the Google charts and visualization API.

D. Load the data into Google BigQuery tables, write a Google Data Studio 360 report that connects to your data, calculates a metric, and then uses a filter expression to show only suboptimal rows in a table.

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Success Stories

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  • Ohio
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