Google Professional-Data-Engineer日本語 exam - in .pdf

Professional-Data-Engineer日本語 pdf
  • Exam Code: Professional-Data-Engineer日本語
  • Exam Name: Google Certified Professional Data Engineer Exam (Professional-Data-Engineer日本語版)
  • Updated: Sep 14, 2026
  • Q & A: 433 Questions and Answers
  • PDF Price: $69.99
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  • Exam Code: Professional-Data-Engineer日本語
  • Exam Name: Google Certified Professional Data Engineer Exam (Professional-Data-Engineer日本語版)
  • Updated: Sep 14, 2026
  • Q & A: 433 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $139.98  $89.99
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Professional-Data-Engineer日本語 Testing Engine
  • Exam Code: Professional-Data-Engineer日本語
  • Exam Name: Google Certified Professional Data Engineer Exam (Professional-Data-Engineer日本語版)
  • Updated: Sep 14, 2026
  • Q & A: 433 Questions and Answers
  • Software Price: $69.99
  • Testing Engine

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Building & Operationalizing Data Processing Systems

Within this subject area, the test takers should show that they know how to build and operationalize storage systems. Specifically, they need to be conversant with effective use of managed services (such as Cloud Bigtable, Cloud SQL, Cloud Spanner, BigQuery, Cloud Storage, Cloud Memorystore, Cloud Datastore), storage costs & performance, and lifecycle management of data. The students should also be capable of building as well as operationalizing pipelines, including such technical tasks as data cleansing, transformation, batch & streaming, data acquisition & import, and integrating with new data sources. Apart from that, the candidates need to have sufficient competency to build and operationalize the processing infrastructure. This includes a good comprehension of provisioning resources, adjusting pipelines, monitoring pipelines, as well as testing & quality control.

The Google Professional Data Engineer certification is designed to equip the individuals with the required knowledge and skills to enable data-driven decision-making through collecting, transforming, and publishing data. To earn this certificate, the candidates will be required to pass a single test measuring their skills in leveraging, deploying, and continuously training pre-existing machine learning models. The qualifying exam also evaluates the ability of the applicants to design, build, operationalize, monitor, and secure data processing systems.

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

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

SectionWeightObjectives
Topic 1: Building and operationalizing data processing systems24%- Data ingestion and integration
  • 1. Batch ingestion pipelines (BigQuery, Cloud Storage)
    • 2. Streaming ingestion (Pub/Sub, Dataflow)
      - Data processing and transformation
      • 1. Using Dataproc, Dataflow, and BigQuery SQL
        • 2. ETL/ELT pipeline design
          Topic 2: 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. Latency, throughput, and consistency trade-offs
                • 2. Event-driven vs batch architectures
                  Topic 3: Operationalizing machine learning models26%- ML pipeline integration
                  • 1. Feature engineering and feature stores
                    • 2. Vertex AI pipeline deployment
                      - Model deployment and monitoring
                      • 1. Online vs batch prediction
                        • 2. Model monitoring and drift detection
                          Topic 4: Ensuring solution quality28%- Reliability and performance
                          • 1. Fault tolerance and recovery strategies
                            • 2. Monitoring pipelines and workloads
                              - Security and governance
                              • 1. Data governance and compliance
                                • 2. IAM and access control in GCP

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