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Google Professional-Data-Engineer exam is a certification offered by Google to those who want to showcase their expertise in designing, building, and maintaining data processing systems on the Google Cloud Platform. Google Certified Professional Data Engineer Exam (Professional-Data-Engineer日本語版) certification is designed for professionals who have a deep understanding of data engineering and can leverage Google Cloud technologies to create scalable and efficient data pipelines. Professional-Data-Engineer-JPN exam assesses the candidate's ability to design data processing systems, build and operationalize data pipelines, and manage and monitor data processing infrastructure.

Professional Data Engineer Exam Details

Like other Google exams, this exam also consists of multiple choice and multiple select questions. Consider the fact that you need to pay $200 for the registration. After that, you will access the test for 2 hours which is presented either in English or Japanese. Moreover, you can either take the exam online or have to find a test center near your place to take this test.

There is no formal prerequisite for the exam but it is recommended to have 3-4 years of experience within the data engineering field and to be responsible for the tasks related to data engineering and machine learning. So, on the final test day, you need to have exhaustive knowledge about these domains to perform your best.

  • Operationalizing machine learning models
  • Building data processing systems
  • Providing solution quality
  • Designing data processing systems

Google Professional-Data-Engineer Certification Exam is an exam offered by Google Cloud that provides individuals with the opportunity to demonstrate their proficiency in designing and building data processing systems on Google Cloud Platform. Google Certified Professional Data Engineer Exam (Professional-Data-Engineer日本語版) certification is intended for individuals who have experience in data processing and have worked with Google Cloud Platform technologies. Google Certified Professional Data Engineer Exam (Professional-Data-Engineer日本語版) certification exam measures a candidate's ability to design, build, operationalize, secure, and monitor data processing systems.

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Google Professional-Data-Engineer: Google Certified Professional Data Engineer Exam is an essential certification exam for professionals looking to advance their careers in the field of data engineering. Passing Professional-Data-Engineer-JPN exam validates a candidate's expertise in designing, building, and managing data processing systems. It also demonstrates their ability to analyze and interpret data, make informed business decisions, and leverage cloud-based data processing systems to achieve business objectives.

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

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

SectionWeightObjectives
Building and operationalizing data processing systems25%- Building data pipelines
  • 1. Transforming and cleaning data
  • 2. Ingesting data from various sources
  • 3. Orchestrating data workflows
- Deploying and managing systems
  • 1. Monitoring and logging data processes
  • 2. Managing infrastructure and resources
Operationalizing machine learning models20%- Deploying and maintaining ML models
  • 1. Optimizing model performance and cost
  • 2. Model serving and monitoring
- Preparing data for ML
  • 1. Feature engineering and data preparation
  • 2. Handling structured and unstructured data
Maintaining and automating data workloads18%- Automation and repeatability
  • 1. Implementing CI/CD for data systems
  • 2. Automating deployment and updates
- Resource optimization
  • 1. Choosing appropriate compute and storage options
  • 2. Cost management and resource allocation
Designing data processing systems20%- Designing for regulatory and security requirements
  • 1. Implementing access control and data protection
  • 2. Ensuring data privacy and compliance
- Designing for business requirements
  • 1. Designing for reliability and fault tolerance
  • 2. Designing for scalability and elasticity
  • 3. Selecting appropriate storage solutions
Ensuring solution quality and reliability17%- Testing and validating data systems
  • 1. Data quality validation
  • 2. Performance and scalability testing
- Troubleshooting and optimization
  • 1. Optimizing queries and workloads
  • 2. Diagnosing performance issues

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