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Google Professional Data Engineer Exam
Last Update: 15-Jun-2025
Questions: 376 Answers With Expert Explanation
Buy Now
Google Professional Data Engineer Exam
Last Update: 15-Jun-2025
Questions: 376
Buy Now
Google Professional Data Engineer Exam
Last Update: 15-Jun-2025
Questions: 376 Answers With Expert Explanation
Buy Now
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by Grant on 30-Apr-2025
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You currently have a single on-premises Kafka cluster in a data center in the us-east region that is responsible for ingesting messages from IoT devices globally. Because large parts of globe have poor internet connectivity, messages sometimes batch at the edge, come in all at once, and cause a spike in load on your Kafka cluster. This is becoming difficult to manage and prohibitively expensive. What is the Google-recommended cloud native architecture for this scenario?
You have data located in BigQuery that is used to generate reports for your company. You have noticed some weekly executive report fields do not correspond to format according to company standards for example, report errors include different telephone formats and different country code identifiers. This is a frequent issue, so you need to create a recurring job to normalize the data. You want a quick solution that requires no coding What should you do?
You are running a Dataflow streaming pipeline, with Streaming Engine and Horizontal Autoscaling enabled. You have set the maximum number of workers to 1000. The input of your pipeline is Pub/Sub messages with notifications from Cloud Storage One of the pipeline transforms reads CSV files and emits an element for every CSV line. The Job performance is low. the pipeline is using only 10 workers, and you notice that the autoscaler is not spinning up additional workers. What should you do to improve performance?
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TESTED 15 Jun 2025