Latest GCP-DE Exam Guide | Reliable GCP-DE Exam Questions

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Google GCP-DE Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Operationalizing data and ML pipelines	30%	- Pipeline automation and orchestration 1. Cloud Composer workflows 2. Scheduling and monitoring pipelines - Monitoring and troubleshooting 1. Performance optimization and debugging 2. Logging and observability
Topic 2: Building and operationalizing data processing systems	30%	- Data pipeline implementation 1. Dataflow pipeline development 2. Dataproc and Spark-based processing - Data ingestion and transformation 1. Pub/Sub streaming ingestion 2. ETL/ELT workflows
Topic 3: Maintaining and optimizing data and ML solutions	20%	- Security and governance 1. Data encryption and compliance 2. IAM and access control - Machine learning integration 1. Vertex AI integration for pipelines 2. BigQuery ML usage
Topic 4: Designing data processing systems	20%	- Data pipeline architecture design 1. Batch vs streaming data processing selection 2. Scalable data ingestion design - Storage and data modeling 1. Data warehouse design using BigQuery 2. Data lake architecture on Google Cloud Storage

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2026 GCP-DE – 100% Free Latest Exam Guide | Perfect Reliable Data Engineer Exam Questions

Candidates who become Google GCP-DE certified demonstrate their worth in the Google field. GCP-DE certification is proof of their competence and skills. This is a highly sought after credential and it makes career advancement easier for the candidate. To become Google GCP-DE Certified, you must pass the Data Engineer (GCP-DE) Exam. For this task, you need actual and updated GCP-DE Questions.

Google Data Engineer Sample Questions (Q21-Q26):

NEW QUESTION # 21
Which of the following job types are supported by Cloud Dataproc (select 3 answers)?

A. YARN
B. Pig
C. Spark
D. Hive

Answer: B,C,D

Explanation:
Cloud Dataproc provides out-of-the box and end-to-end support for many of the most popular job types, including Spark, Spark SQL, PySpark, MapReduce, Hive, and Pig jobs.
Reference: https://cloud.google.com/dataproc/docs/resources/faq#what_type_of_jobs_can_i_run

NEW QUESTION # 22
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 Spanner, and insert and delete rows with the job information
B. Use a Cloud Pub/Sub topic to publish jobs, and use subscriptions to execute them
C. Create a table on Cloud SQL, and insert and delete rows with the job information
D. Create an API using App Engine to receive and send messages to the applications

Answer: B

NEW QUESTION # 23
Suppose you have a table that includes a nested column called "city" inside a column called "person", but when you try to submit the following query in BigQuery, it gives you an error.
SELECT person FROM `project1.example.table1` WHERE city = "London"
How would you correct the error?

A. Change "person" to "person.city".
B. Add ", UNNEST(city)" before the WHERE clause.
C. Change "person" to "city.person".
D. Add ", UNNEST(person)" before the WHERE clause.

Answer: D

Explanation:
To access the person.city column, you need to "UNNEST(person)" and JOIN it to table1 using a comma. Reference:
https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#nested_repeated_resu

NEW QUESTION # 24
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 a view on the table to present to the virtualization tool.
B. Create identity and access management (IAM) roles on the appropriate columns, so only they appear in a query.
C. Create an additional table with only the necessary columns.
D. Export the data into a Google Sheet for virtualization.

Answer: A

NEW QUESTION # 25
MJTelco needs you to create a schema in Google Bigtable that will allow for the historical analysis of the last 2 years of records. Each record that comes in is sent every 15 minutes, and contains a unique identifier of the device and a data record. The most common query is for all the data for a given device for a given day. Which schema should you use?

A. Rowkey: date#device_idColumn data: data_point
B. Rowkey: date#data_pointColumn data: device_id
C. Rowkey: device_idColumn data: date, data_point
D. Rowkey: data_pointColumn data: device_id, date
E. Rowkey: dateColumn data: device_id, data_point

Answer: D

NEW QUESTION # 26
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