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Google Professional-Data-Engineer日本語 Test Passed : Google Certified Professional Data Engineer Exam (Professional-Data-Engineer日本語版)

Professional-Data-Engineer日本語 actual test
  • Exam Code: Professional-Data-Engineer-JPN
  • Exam Name: Google Certified Professional Data Engineer Exam (Professional-Data-Engineer日本語版)
  • Updated: Jul 27, 2026
  • Q & A: 433 Questions and Answers
  • PDF Demo
  • PC Test Engine
  • Online Test Engine
  • Total Price: $69.99  

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Understanding functional and technical aspects of Google Professional Data Engineer Exam Operationalizing machine learning models

The following will be discussed here:

  • Hardware accelerators (e.g., GPU, TPU)
  • Retraining of machine learning models (Cloud Machine Learning Engine, BigQuery ML, Kubeflow, Spark ML)
  • Machine learning terminology (e.g., features, labels, models, regression, classification, recommendation, supervised and unsupervised learning, evaluation metrics)
  • Ingesting appropriate data
  • Impact of dependencies of machine learning models
  • Measuring, monitoring, and troubleshooting machine learning models
  • Customizing ML APIs (e.g., AutoML Vision, Auto ML text)
  • Choosing the appropriate training and serving infrastructure
  • Leveraging pre-built ML models as a service
  • Continuous evaluation
  • Deploying an ML pipeline
  • Conversational experiences (e.g., Dialogflow)
  • Use of edge compute
  • Common sources of error (e.g., assumptions about data)
  • ML APIs (e.g., Vision API, Speech API)
  • Operationalizing machine learning models
  • Distributed vs. single machine

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Exam Overview

The Professional Data Engineer certification exam is a 2-hour test consisting of the multiple-choice and multiple-select questions. The students can take it in the English or Japanese languages. To register for and schedule the exam, you must pay the fee of $200. It is possible to sit for this test in an online proctored format at a remote location. You can also take it as an on-site proctored exam at a designated testing center.

Reference: https://cloud.google.com/certification/data-engineer

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Career Opportunities

The certified individuals can explore a variety of job opportunities. Some of the positions that they can take up include a Software Engineer, a Cloud Architect, a Data Engineer, a Sales Engineer, a Data Scientist, a Cloud Developer, and a Kubernetes Architect, among others. The salary outlook for these job roles is an average of $128,500 per annum.

Google Professional-Data-Engineer日本語 Exam Syllabus Topics:

SectionWeightObjectives
Ensuring solution quality28%- Security and governance
  • 1. IAM and access control in GCP
    • 2. Data governance and compliance
      - Reliability and performance
      • 1. Monitoring pipelines and workloads
        • 2. Fault tolerance and recovery strategies
          Designing data processing systems22%- Data architecture and storage design
          • 1. Choosing appropriate data storage solutions (relational, NoSQL, data warehouse)
            • 2. Designing scalable and cost-effective data models
              - Batch and streaming data processing design
              • 1. Event-driven vs batch architectures
                • 2. Latency, throughput, and consistency trade-offs
                  Operationalizing machine learning models26%- Model deployment and monitoring
                  • 1. Model monitoring and drift detection
                    • 2. Online vs batch prediction
                      - ML pipeline integration
                      • 1. Vertex AI pipeline deployment
                        • 2. Feature engineering and feature stores
                          Building and operationalizing data processing systems24%- Data processing and transformation
                          • 1. ETL/ELT pipeline design
                            • 2. Using Dataproc, Dataflow, and BigQuery SQL
                              - Data ingestion and integration
                              • 1. Streaming ingestion (Pub/Sub, Dataflow)
                                • 2. Batch ingestion pipelines (BigQuery, Cloud Storage)

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