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Google Professional-Data-Engineer
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Google Professional-Data-Engineer Questions and Answers
You need to store and analyze social media postings in Google BigQuery at a rate of 10,000 messages per minute in near real-time. Initially, design the application to use streaming inserts for individual postings. Your application also performs data aggregations right after the streaming inserts. You discover that the queries after streaming inserts do not exhibit strong consistency, and reports from the queries might miss in-flight data. How can you adjust your application design?
You are designing a basket abandonment system for an ecommerce company. The system will send a message to a user based on these rules:
No interaction by the user on the site for 1 hour
Has added more than $30 worth of products to the basket
Has not completed a transaction
You use Google Cloud Dataflow to process the data and decide if a message should be sent. How should you design the pipeline?
Your company’s on-premises Apache Hadoop servers are approaching end-of-life, and IT has decided to migrate the cluster to Google Cloud Dataproc. A like-for-like migration of the cluster would require 50 TB of Google Persistent Disk per node. The CIO is concerned about the cost of using that much block storage. You want to minimize the storage cost of the migration. What should you do?
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With the complete collection of Professional-Data-Engineer practice test, Exams4sure has assembled to take you through Google Cloud Certified test questions for your Google exam preparation. In this Professional-Data-Engineer exam dumps study guide we have compiled real Google Professional Data Engineer Exam exam questions with their answers so that you can prepare and pass Google Cloud Certified exam in your first attempt.
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The role of a Professional Data Engineer in Google Cloud involves designing, building, and maintaining data processing systems that are scalable, efficient, and reliable. They work with large datasets to extract insights, drive business decisions, and optimize data-driven processes.
A Professional Data Engineer makes data usable and valuable for others by designing data processing pipelines that transform raw data into meaningful insights. They ensure data quality, implement data governance practices, and create intuitive interfaces for accessing and analyzing data.
The key responsibilities of a Professional Data Engineer in data processing include designing and implementing data pipelines, integrating data from various sources, cleaning and transforming data, optimizing data storage and retrieval, and ensuring data security and compliance.
The exam assesses the ability to design data processing systems by testing candidates on their understanding of data processing concepts, their knowledge of Google Cloud Platform (GCP) data processing services, their proficiency in designing scalable and efficient data pipelines, and their ability to optimize data processing workflows for performance and cost efficiency.
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United States Are these Professional Data Engineer practice questions and answers still valid?
TESTED 15 Oct 2025
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