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Google Cloud Professional Data Engineer

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Google Cloud Professional Data Engineer

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Overview
Curriculum
Last updated 11/2024

 

Google Cloud Professional Data Engineer.

 

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GCP PDE Google Cloud Professional Cloud Data Engineer Practice Exam & Test Questions | Google Cloud Platform Certification Course | Official Latest Exams Syllabus Practice Tests | Exam Guide | Detailed Solution Explanations + Reference Links

 

Keywords: google cloud professional data engineer, google cloud professional cloud data engineer, google data engineer certification, gcp data engineer certification, gcp data engineer, google cloud data engineer certification, google certified data engineer, google cloud platform data engineer certification, google cloud certified data engineer

Curriculum

  • 2 Sections
  • 201 Lessons
  • 0m Duration
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EXAM TIPS
1 Lesson
  1. README
QUESTIONS, ANSWERS, & SOLUTIONS
200 Lessons
  1. You have more than a petabyte of data in your on-premises data center that you want to migrate to Google Cloud.
  2. You are working as a Data Scientist at a major airline.
  3. You are building a chatbot using Dialogflow to streamline customer support processes.
  4. You work at a large enterprise that has 40 TB of user activity data.
  5. As a Data Engineer at a retail company, you've developed a Spark ML model for forecasting advertisement click-through rates.
  6. You're employed at a manufacturing company with a vast 8 TB sales dataset earmarked for machine learning purposes.
  7. You are in the process of revamping your batch pipeline to accommodate structured data on Google Cloud.
  8. You have collected data regarding ads from various sources that you plan to use to serve AI models and analyze historical trends.
  9. You work at a large hospital chain that has accumulated 15 TB of medical data in its database.
  10. You're employed at a major bank, tasked with constructing a recommendation engine using streaming data files that may contain PII (personally identifiable information) data.
  11. You're using Cloud Composer to manage ETL pipelines.
  12. You work at a company that develops apps for stock market trading.
  13. You're at a shipping company that uses a live stream in Apache Kafka to track shipments.
  14. You need to give new website users a globally unique identifier (GUID) using a service that takes in data points and returns a GUID.
  15. You are employed at a financial institution considering Cloud Storage for storing archived data securely.
  16. You are working on a new Data Analytics project in your company that is going to use MySQL.
  17. You work at a logistics company where you've developed a data processing system utilizing Apache Kafka to handle live data streams, feeding them into BigQuery in real time.
  18. As the head of Data Engineering in your company, you're seeking a system to centralize data ingestion and delivery.
  19. You work as a Data Engineer at a startup.
  20. You're involved in a large-scale migration of your on-premises data center to Google Cloud Platform (GCP), with a key focus on migrating the company's data warehouse.
  21. You have two teams, namely the development team and the testing team working on the same GCP project.
  22. You have a movie database within your on-premises data warehouse slated for migration to BigQuery.
  23. You're on the SRE team at your company.
  24. You are the Chief Data Officer at an enterprise that is looking for a suitable database for a new project.
  25. You have built a Dataflow pipeline for ingesting and transforming text files, with the files being compressed gzip, errors directed to a dead-letter queue, and SideInputs utilized for data joining.
  26. You are working on an application that spans multiple projects in Google Cloud.
  27. You've uploaded several years of log data to Cloud Storage, utilized by analysts for generating insights.
  28. As a Senior Data Engineer at your company, you're immersed in a binary classification project.
  29. You're a member of the Data Operations team tasked with overseeing data pipelines on BigQuery, Dataflow, and Dataproc.
  30. You work at a retail company.
  31. You are employed at a machine learning startup and face the task of deploying additional dependencies to all nodes of a Cloud Dataproc cluster during startup, leveraging an existing initialization action.
  32. As the lead engineer orchestrating your company's data warehousing solution on Google Cloud, you're leveraging BigQuery and shaping the data model.
  33. You work for a financial institution that lets customers register online.
  34. You work at a manufacturing company that has 10 TB of data in their co-located data center that they want to migrate to GCP.
  35. You're a Data Engineer in charge of handling batch jobs on Dataflow.
  36. You are working as a Devops Engineer tasked with migrating a Redis database from an on-premises data center to a Memorystore for Redis instance.
  37. You work at a startup with an app operating in just one region in Asia.
  38. You are tasked with overseeing a substantial cluster consisting of Spark, Hive, and HDFS within your on-premises data center.
  39. You're creating a data warehouse just for making reports.
  40. You are working at a major retail company.
  41. You are leading the transition from an on-premises Apache Hadoop setup to Google Cloud, aiming for fault tolerance and cost efficiency in long-running batch operations.
  42. You work at a financial institution based in North America, where your team is developing a new application mandating ACID compliance and SQL data access.
  43. As a DevOps Engineer responsible for migrating your company's operational system transaction data from an on-premises database to GCP, you're facing a 15 TB database size.
  44. As the lead Data Engineer at your firm, you're responsible for designing a pipeline to publish events to a Pub/Sub topic.
  45. You're developing an app to analyze a company's stock by computing a moving average based on the past 30 seconds of data.
  46. You are building software to predict customer preferences.
  47. You are working as an ML-Ops engineer at a medium-scale business.
  48. As a Data Engineer, you're responsible for migrating a table to BigQuery, which holds data on purchases across multiple store locations, including transaction time, items purchased, store ID, and store location (city and state).
  49. You're gathering data from tons of IoT sensors worldwide and saving it in BigQuery.
  50. You're employed at a big enterprise with business operations spanning various sectors like travel, life sciences, and automotive.
  51. You're creating an app for people to vote during a live cricket match.
  52. You are the Chief Data Officer at your company, where you are designing a data mesh on Google Cloud with several different teams building data products.
  53. As a Data Scientist, you're developing a linear regression model in BigQuery ML to forecast customer purchase likelihood for your company's products.
  54. You have an app running on-premises that generates 120 GB of data every day.
  55. You're at an IT services firm, handling a project to transfer your client's data to BigQuery.
  56. You're building a model to guess stock prices using machine learning.
  57. You are working at an E-commerce company as a Data Engineer.
  58. You have a Dataflow pipeline that is having some issues.
  59. You are a Cloud Architect who is designing a new app for your company.
  60. You have a BigQuery table that stores customer info, including sensitive stuff like names and addresses.
  61. You are working as a Data Engineer at a large enterprise.
  62. You are part of the Data Engineering team at your company.
  63. You have built an analytics dashboard using a SQL-based tool with BigQuery.
  64. You are using Cloud Composer 2 to deploy several data processing jobs.
  65. You are planning to use machine learning for forecasting customer conversion rates.
  66. As a DevOps engineer, you're setting up a MySQL database workload on Cloud SQL.
  67. Your team runs both ad-hoc queries and scheduled SQL pipelines in BigQuery, using a reservation of 2000 slots.
  68. Your company's data platform receives CSV file dumps of booking and user profile data from upstream sources, storing them in Cloud Storage.
  69. As a Data Engineer, you're handling an Apache Beam pipeline.
  70. You're prepping data for training a model to predict real estate prices, and you're planning to use BigQueryML for the training.
  71. You have a Cloud SQL for PostgreSQL setup in Region1 with read replicas in Region2 and Region3.
  72. As a Data Engineer, you oversee a Data Warehouse on BigQuery.
  73. You are responsible for managing a Dataflow streaming pipeline, utilizing Streaming Engine and Horizontal Auto Scaling features with the maximum number of workers configured to be 1000.
  74. You're a Data Engineer setting up an Apache Beam pipeline to get data from a Cloud SQL instance using JdbcIO.
  75. As the Chief Data Officer of a medium-sized enterprise, you're transitioning your data strategy from on-premises to Google Cloud.
  76. You are employed at a Game Development company managing a substantial fleet of custom virtual machines serving as game servers.
  77. You have an app that is used by users in your country, that uses Data Studio to display reports on large quantities of aggregated data.
  78. As the lead Data Engineer at a telecom company, you're responsible for designing the company's Data Warehouse.
  79. You are a Data Scientist who wants to build machine learning models using a large collection of files in Cloud Storage.
  80. You are a Data Analyst building a pipeline to schedule workflows using open-source-based tools.
  81. You've set up a Standard Tier Memorystore for Redis in your GCP project.
  82. You created a workflow to handle data on Google Kubernetes Engine (GKE).
  83. You are working at a large E-commerce company.
  84. As an architect, you're planning an app that relies on Cloud Storage for data storage.
  85. You are part of the security team at your company and you need to release security requirements to deploy resources.
  86. You're part of the data analytics team in your company, responsible for managing an IoT pipeline centered around Apache Kafka, typically handling about 6000 messages per second.
  87. You are streaming order data with a Dataflow pipeline and storing the aggregated result in Memorystore.
  88. You have an Oracle database running in your VPC.
  89. You have an Apache Hadoop cluster in your on-premises data center, storing data in Apache Parquet format.
  90. You are building a Machine Learning model using data using data from various types of files, such as Apache Parquet and CSV, all stored in a Cloud Storage bucket.
  91. You work at a stock brokerage firm.
  92. You plan to use BigQuery ML to create a recommendation engine.
  93. As an application developer constructing an app reliant on Pub/Sub subscription feeds, you are afraid of potential message loss due to erroneous acknowledgment upon deployment, especially since your subscriber isn't configured to retain acknowledged messages.
  94. You're tasked with refining and organizing data to construct analytics dashboards for your management team.
  95. You are in charge of migrating the data storage for an app that handles 10 PB of old product data for analysis to Google Cloud.
  96. Your BigQuery project is configured to run in the on-demand billing model.
  97. You work as a Data Engineer and handle your company’s BigQuery data warehouse.
  98. You're employed at a B2B company that handles sensitive data from multiple customers.
  99. You are building a Data Lake for a client, a steel manufacturing company.
  100. You have VM data inventory in the form of the below table.
  101. You're the lead Data Engineer for an in-house project with several steps to load and transform data.
  102. You're setting up an SQL pipeline that conducts an aggregate SQL transformation on a BigQuery table every two hours and adds the output to another pre-existing BigQuery table.
  103. You're an architect at a consulting firm, designing a data mesh on Google Cloud for a client.
  104. You're dealing with a BigQuery dataset containing customer addresses.
  105. Your company has several teams heavily relying on BigQuery.
  106. You have 10 TB of historical data stored in BigQuery tables for performing analysis, with new data incorporated into the tables daily.
  107. You are working at a company specializing in sensors utilized in factories to monitor noise levels.
  108. You're utilizing BigQuery to construct a data model using retail transaction data.
  109. You are part of the Data Governance team at your company.
  110. You are reading data from a Pub/Sub topic and writing it to BigQuery using a Dataflow streaming ingestion pipeline.
  111. Your company uses various Google Cloud data services to manage its data, which is spread across BigQuery, Pub/Sub, and a PostgreSQL instance hosted on Compute Engine.
  112. You have a data lake on BigQuery.
  113. Your company uses BigQuery in several different ways in different projects.
  114. Your team maintains numerous tables in BigQuery, and you aim to store them within a single dataset to facilitate collaboration among team members.
  115. You have built a system that loads Pub/Sub messages into BigQuery, where the data is encrypted with a Google-managed encryption key.
  116. You are working as a Data Engineer at a logistics company.
  117. You have 50 GB of data in your on-premises data center that you want to load into BigQuery.
  118. You're tasked with setting up a new data analytics platform on Google Cloud for your company.
  119. As a Data Scientist at a retail company, you are involved in creating a Dataflow pipeline for a batch processing task.
  120. You are working as a Developer at a ride-hailing app company, working on a feature to determine taxi demand in an area and adjust fares accordingly.
  121. You are working at a large enterprise that is using BigQuery as their Data Warehouse.
  122. You're utilizing hopping windows to group incoming data within a streaming pipeline using Dataflow.
  123. You are a member of the Data Engineering team at a retail company.
  124. You have a streaming pipeline with Dataflow, where one of the tasks consumes messages from a message queue lacking support for exactly-once delivery.
  125. You are working at a large enterprise with assets spread across multiple cloud platforms.
  126. You are investigating slowness in queries against an external table for Apache Hive whose partitioned data is stored in a Cloud Storage bucket as thousands of files.
  127. Your company specializes in developing IoT products for industrial applications.
  128. As the Chief Data Officer of a startup, you plan to follow Google's security recommendations by implementing encryption measures for all data in BigQuery.
  129. You're preparing to transfer roughly 150 TB of historical data from your on-premises setup to a BigQuery table.
  130. You are working at a finance company that stores important contract-related documents on BigQuery.
  131. You're managing an on-premises Apache Hadoop setup that handles numerous Apache Spark jobs.
  132. You oversee the administration of shared BigQuery datasets containing views utilized by various teams within your organization.
  133. You are a member of a healthcare organization where data is handled by different owners across various storage platforms.
  134. Multiple teams within your company utilize analytics data stored in BigQuery to generate reports and conduct analyses.
  135. Your team is constructing a data lake platform on Google Cloud.
  136. You are developing a product that utilizes Pub/Sub to manage clickstream data, with an event-driven consumer app relying on a push subscription.
  137. As a Data Engineer, your task is to deploy an Apache Airflow directed acyclic graph (DAG) within a Cloud Composer 2 instance.
  138. You are designing a data warehouse for your company.
  139. You're developing a batch pipeline within Dataflow, which involves reading data from Cloud Storage, processing it, and finally storing it in BigQuery.
  140. Your company operates its workloads across on-premises data centers and various cloud providers.
  141. You are working at an E-commerce company.
  142. You are leading your company’s initiative of getting rid of its legacy on-premise data center and migrating to Google Cloud.
  143. You work as a Data Engineer at a retail company.
  144. You are working as a Lead Architect for a project for a data processing pipeline using Dataflow.
  145. You have a Teradata data warehouse that you plan to migrate to BigQuery.
  146. You are a Data Architect working on a hybrid cloud solution for streaming data from an on-premise Apache Kafka cluster hosted on-premises to Google Cloud.
  147. You have a data lake on Apache Hadoop Distributed File System (HDFS) that you are migrating to Cloud Storage.
  148. You're facing a situation where one of the keys your team stored in Cloud Key Management Service (Cloud KMS) got leaked online.
  149. You are employed at a retail corporation with a long-standing customer loyalty program.
  150. You're a Data Engineer working on a Data pipeline where data gets written to Cloud Storage by an upstream process.
  151. You're a member of the team responsible for maintaining ETL pipelines at your company.
  152. You're employed at an E-commerce company.
  153. As a consultant for a car manufacturing company, your goal is to build a system for detecting imperfections in their vehicles.
  154. You're employed at a manufacturing company, where your team is developing an application to streamline customer order processing via Google Cloud.
  155. You are building a high-performance API that will be consumed by multiple third-party companies to build integrations in their applications.
  156. You have important customer data stored in Cloud Spanner.
  157. You're involved in a project aimed at modernizing the trading platform for a stock exchange catering to millions of traders.
  158. You have developed a data processing solution using Dataproc, which currently takes approximately 45 minutes to handle a workload.
  159. You are employed at a company that makes IoT devices that transmit data to Pub/Sub.
  160. You have a directed acyclic graph (DAG) running in Cloud Composer, that your boss has asked you to automate using CI/CD.
  161. You're developing an application that executes a daily query on a BigQuery table.
  162. Your company builds devices that users wear to monitor their health.
  163. You have a Cloud SQL instance with an external IP address that needs to be accessed from your team’s laptops which are connected to the public internet.
  164. As a Data Engineer overseeing your company's Dataplex environment, you're tasked with administering raw and curated zones.
  165. You are employed at an E-commerce enterprise.
  166. You're creating a new app and need to collect data from it in a scalable manner.
  167. You are employed at a stock market management company and are developing a new product tailored for brokers to access real-time stock data.
  168. Your company manufactures IoT devices for agricultural use.
  169. You have an application that stores order-related data in BigQuery.
  170. You are working as a Data Engineer running a pipeline in Dataflow where messages from a Pub/Sub topic get sent to a BigQuery dataset in the EU.
  171. Your company specializes in constructing autonomous drones utilized for surveying landscapes, and continuously transmitting data like location, speed, etc., to your servers.
  172. You are a Developer at an E-commerce firm where the website relies on PostgreSQL as its primary database.
  173. As the chief data officer of your company, you oversee a team of proficient business analysts.
  174. You manage an SQL Server database housing approximately 5 TB of data within your on-premises data center, with anticipated growth to a maximum of 25 TB.
  175. You're a member of the technology team at a major logistics company.
  176. You are a lead architect building a data processing pipeline.
  177. You are building an app that automatically analyzes stock market patterns and provides personalized recommendations to users.
  178. You are part of a team responsible for overseeing a Cloud Dataflow streaming pipeline.
  179. You recently migrated your company’s 100 TB data warehouse to BigQuery.
  180. You are a Data Engineer handling multiple data processing jobs within your company.
  181. You're employed by a company with a weather forecast app, and as part of a modernization effort, you're strategizing to utilize BigQuery for storing weather data.
  182. You are managing a BigQuery dataset, where your team executes a daily query to generate user recommendations.
  183. You have 3 PB of data stored in persistent disks in your on-premises data center that you want to migrate to Cloud Storage.
  184. As a member of the Cloud Support team within your organization, your task is to link multiple applications, each with dynamic public IP addresses, to a Cloud SQL instance.
  185. You're employed at a fintech firm specializing in stock market monitoring.
  186. Your app is built using the microservices framework.
  187. As a Data architect creating a historical data processing system on Google Cloud, you need to ensure that it meets specific requirements.
  188. You operate Hadoop and Spark clusters to conduct data analysis in your on-premises environment.
  189. Your company has a large dataset in BigQuery that is used by multiple teams to perform analysis.
  190. You are part of the Cloud Governance team at your company.
  191. You are a data architect crafting a data transformation solution tailored for BigQuery.
  192. As the lead architect overseeing the migration of a substantial volume of files from a public HTTPS endpoint to Cloud Storage, your responsibility includes ensuring the security of these files via signed URLs.
  193. You have developed an application that uses Bigtable as its database.
  194. You are working as a Data Engineer facilitating your company’s marketing team in managing customer data in BigQuery.
  195. You are operating a Kafka cluster in a data center owned by your company, located in the us-east region.
  196. You oversee a complex data pipeline on Google Cloud that you aim to automate.
  197. Your company has a Machine Learning model for generating user recommendations.
  198. You work at a tech company making smart wearables.
  199. You've recently adopted BigQuery for data analysis, transitioning from an on-premises data warehouse setup.
  200. You are developing a proof of concept solution for forecasting delivery times within a food delivery application.

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