Free PDF 2026 GCP-DE: High-quality Data Engineer Key Concepts

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The Data Engineer (GCP-DE) certification exam is one of the top-rated and career-oriented certificates that are designed to validate an Google professional's skills and knowledge level. These Data Engineer (GCP-DE) practice questions have been inspiring those who want to prove their expertise with the industrial-recognized credential. By cracking it you can gain several personal and professional benefits.

Google GCP-DE Exam Syllabus Topics:

Section	Weight	Objectives
Storing and managing data	20%	- Optimizing storage performance and cost 1. Implementing cost optimization strategies 2. Configuring storage for access patterns - Implementing storage solutions 1. Using data storage services appropriately 2. Designing data warehouses and data lakes 3. Managing data lifecycle and retention
Maintaining and automating data workloads	18%	- Operationalizing workloads 1. Orchestrating and scheduling jobs 2. Ensuring reliability and recoverability 3. Monitoring and troubleshooting pipelines - Automation and optimization 1. Automating deployment and management 2. Optimizing resource usage and costs
Preparing data for analysis and machine learning	13%	- Enabling data analysis 1. Implementing data sharing and governance 2. Optimizing query performance 3. Preparing datasets for querying and reporting - Preparing data for ML 1. Feature engineering and data preparation 2. Supporting model training and serving
Ingesting and processing data	25%	- Building data pipelines 1. Handling data quality and consistency 2. Implementing ingestion mechanisms 3. Developing batch and streaming workflows - Transforming data 1. Optimizing transformations for performance 2. Applying data processing logic 3. Managing schema evolution
Designing data processing systems	24%	- Designing data pipelines 1. Defining architecture for batch and streaming processing 2. Planning for data migration and integration 3. Designing for data transformation and enrichment - Planning data solutions 1. Planning for data security and compliance 2. Selecting appropriate storage solutions 3. Designing for reliability, scalability, and efficiency

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GCP-DE Key Concepts Exam Pass at Your First Attempt | Google GCP-DE: Data Engineer

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Google Data Engineer Sample Questions (Q75-Q80):

NEW QUESTION # 75
You are building a new data pipeline to share data between two different types of applications: jobs generators and job runners. Your solution must scale to accommodate increases in usage and must accommodate the addition of new applications without negatively affecting the performance of existing ones. What should you do?

A. Create a table on Cloud SQL, and insert and delete rows with the job information
B. Create a table on Cloud Spanner, and insert and delete rows with the job information
C. Create an API using App Engine to receive and send messages to the applications
D. Use a Cloud Pub/Sub topic to publish jobs, and use subscriptions to execute them

Answer: D

NEW QUESTION # 76
You are operating a Cloud Dataflow streaming pipeline. The pipeline aggregates events from a Cloud Pub/Sub subscription source, within a window, and sinks the resulting aggregation to a Cloud Storage bucket. The source has consistent throughput. You want to monitor an alert on behavior of the pipeline with Cloud Stackdriver to ensure that it is processing dat a. Which Stackdriver alerts should you create?

A. An alert based on a decrease of instance/storage/used_bytes for the source and a rate of change increase of subscription/num_undelivered_messages for the destination
B. An alert based on an increase of subscription/num_undelivered_messages for the source and a rate of change decrease of instance/storage/used_bytes for the destination
C. An alert based on an increase of instance/storage/used_bytes for the source and a rate of change decrease of subscription/num_undelivered_messages for the destination
D. An alert based on a decrease of subscription/num_undelivered_messages for the source and a rate of change increase of instance/storage/used_bytes for the destination

Answer: B

NEW QUESTION # 77
Flowlogistic's CEO wants to gain rapid insight into their customer base so his sales team can be better informed in the field. This team is not very technical, so they've purchased a visualization tool to simplify the creation of BigQuery reports. However, they've been overwhelmed by all the data in the table, and are spending a lot of money on queries trying to find the data they need. You want to solve their problem in the most cost-effective way. What should you do?

A. Create identity and access management (IAM) roles on the appropriate columns, so only they appear in a query.
B. Create a view on the table to present to the virtualization tool.
C. Create an additional table with only the necessary columns.
D. Export the data into a Google Sheet for virtualization.

Answer: B

NEW QUESTION # 78
The YARN ResourceManager and the HDFS NameNode interfaces are available on a Cloud Dataproc cluster .

A. conditional node
B. worker node
C. master node
D. application node

Answer: C

Explanation:
The YARN ResourceManager and the HDFS NameNode interfaces are available on a Cloud Dataproc cluster master node. The cluster master-host-name is the name of your Cloud Dataproc cluster followed by an -m suffix-for example, if your cluster is named "my-cluster", the master-host-name would be "my-cluster-m". Reference: https://cloud.google.com/dataproc/docs/concepts/cluster-web-interfaces#interfaces

NEW QUESTION # 79
You are building a new application that you need to collect data from in a scalable way. Data arrives continuously from the application throughout the day, and you expect to generate approximately 150 GB of JSON data per day by the end of the year. Your requirements are: Decoupling producer from consumer Space and cost-efficient storage of the raw ingested data, which is to be stored indefinitely Near real-time SQL query Maintain at least 2 years of historical data, which will be queried with SQ Which pipeline should you use to meet these requirements?

A. Create an application that provides an AP
B. Create an application that publishes events to Cloud Pub/Sub, and create Spark jobs on Cloud Dataproc to convert the JSON data to Avro format, stored on HDFS on Persistent Disk.
C. Set up periodic exports of the database to write to Cloud Storage and load into BigQuery.
D. Create an application that writes to a Cloud SQL database to store the dat
E. Write a tool to poll the API and write data to Cloud Storage as gzipped JSON files.
F. Create an application that publishes events to Cloud Pub/Sub, and create a Cloud Dataflow pipeline that transforms the JSON event payloads to Avro, writing the data to Cloud Storage and BigQuery.

Answer: A

NEW QUESTION # 80
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