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Professional-Data-Engineer Dumps With Exact Questions and Answers

Exact2pass Provides 100% Valid Google Professional Data Engineer Exam Professional-Data-Engineer Exam dumps Questions and answers which can helps you to Pass Your Certification Exam in First Attempt.

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Professional-Data-Engineer Questions and Answers

Question # 1

MJTelco is building a custom interface to share data. They have these requirements:

  • They need to do aggregations over their petabyte-scale datasets.
  • They need to scan specific time range rows with a very fast response time (milliseconds).

Which combination of Google Cloud Platform products should you recommend?


Cloud Datastore and Cloud Bigtable


Cloud Bigtable and Cloud SQL


BigQuery and Cloud Bigtable


BigQuery and Cloud Storage

Question # 2

MJTelco needs you to create a schema in Google Bigtable that will allow for the historical analysis of the last 2 years of records. Each record that comes in is sent every 15 minutes, and contains a unique identifier of the device and a data record. The most common query is for all the data for a given device for a given day. Which schema should you use?


Rowkey: date#device_idColumn data: data_point


Rowkey: dateColumn data: device_id, data_point


Rowkey: device_idColumn data: date, data_point


Rowkey: data_pointColumn data: device_id, date


Rowkey: date#data_pointColumn data: device_id

Question # 3

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

  • Telemetry must include data from all 50,000 installations for the most recent 6 weeks (sampling once every minute)
  • The report must not be more than 3 hours delayed from live data.
  • The actionable report should only show suboptimal links.
  • Most suboptimal links should be sorted to the top.
  • Suboptimal links can be grouped and filtered by regional geography.
  • User response time to load the report must be <5 seconds.

You create a data source to store the last 6 weeks of data, and create visualizations that allow viewers to see multiple date ranges, distinct geographic regions, and unique installation types. You always show the latest data without any changes to your visualizations. You want to avoid creating and updating new visualizations each month. What should you do?


Look through the current data and compose a series of charts and tables, one for each possible

combination of criteria.


Look through the current data and compose a small set of generalized charts and tables bound to criteria filters that allow value selection.


Export the data to a spreadsheet, compose a series of charts and tables, one for each possible

combination of criteria, and spread them across multiple tabs.


Load the data into relational database tables, write a Google App Engine application that queries all rows, summarizes the data across each criteria, and then renders results using the Google Charts and visualization API.

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