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Google Professional Data Engineer Actual Exam Questions

307 Questions120 Minutes70% Passing Score▣ Updated: Sep 2026

Question 143 of 307

Single answer
You need ads data to serve AI models and historical data for analytics. Longtail and outlier data points need to be identified. You want to cleanse the data in near-real time before running it through AI models. What should you do?
AUse Cloud Storage as a data warehouse, shell scripts for processing, and BigQuery to create views for desired datasets.
BUse Dataflow to identify longtail and outlier data points programmatically, with BigQuery as a sink.
CUse BigQuery to ingest, prepare, and then analyze the data, and then run queries to create views.
DUse Cloud Composer to identify longtail and outlier data points, and then output a usable dataset to BigQuery.
Correct Answer: B

Use Dataflow to identify longtail and outlier data points programmatically, with BigQuery as a sink.

Explanation

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