Login / Register
Sharpen Your Knowledge with Google (Google Cloud Certified Professional Data Engineer) Certification Sample Questions
CertsTime has provided you with a sample question set to elevate your knowledge about the Google Cloud Certified Professional Data Engineer exam. With these updated sample questions, you can become quite familiar with the difficulty level and format of the real Google Cloud Certified Professional Data Engineer certification test. Try our sample Google Cloud Certified Professional Data Engineer certification practice exam to get a feel for the real exam environment. Our sample practice exam gives you a sense of reality and an idea of the questions on the actual Google Cloud Certified certification exam.
Our sample questions are similar to the Real Google Cloud Certified Professional Data Engineer exam questions. The premium Google Cloud Certified Professional Data Engineer certification practice exam gives you a golden opportunity to evaluate and strengthen your preparation with real-time scenario-based questions. Plus, by practicing real-time scenario-based questions, you will run into a variety of challenges that will push you to enhance your knowledge and skills.
Google Cloud Certified Professional Data Engineer Sample Questions:
You are testing a Dataflow pipeline to ingest and transform text files. The files are compressed gzip, errors are written to a dead-letter queue, and you are using Sidelnputs to join data You noticed that the pipeline is taking longer to complete than expected, what should you do to expedite the Dataflow job?
You are using Cloud Bigtable to persist and serve stock market data for each of the major indices. To serve the trading application, you need to access only the most recent stock prices that are streaming in How should you design your row key and tables to ensure that you can access the data with the most simple query?
Your company is implementing a data warehouse using BigQuery, and you have been tasked with designing the data model You move your on-premises sales data warehouse with a star data schema to BigQuery but notice performance issues when querying the data of the past 30 days Based on Google's recommended practices, what should you do to speed up the query without increasing storage costs?
You are building a teal-lime prediction engine that streams files, which may contain Pll (personal identifiable information) data, into Cloud Storage and eventually into BigQuery You want to ensure that the sensitive data is masked but still maintains referential Integrity, because names and emails are often used as join keys How should you use the Cloud Data Loss Prevention API (DLP API) to ensure that the Pll data is not accessible by unauthorized individuals?
You want to rebuild your batch pipeline for structured data on Google Cloud You are using PySpark to conduct data transformations at scale, but your pipelines are taking over twelve hours to run To expedite development and pipeline run time, you want to use a serverless tool and SQL syntax You have already moved your raw data into Cloud Storage How should you build the pipeline on Google Cloud while meeting speed and processing requirements?
Note: If there is any error in our Google Cloud Certified Professional Data Engineer certification exam sample questions, please update us via email at support@certstime.com.
