Microsoft Design and Implement Big Data Analytics Solutions (70-475日本語版) : 70-475日本語

  • Exam Code: 70-475日本語
  • Exam Name: Design and Implement Big Data Analytics Solutions (70-475日本語版)
  • Updated: Aug 05, 2026
  • Q & A: 122 Questions and Answers

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About Microsoft 70-475日本語 Exam

High level topics covered by our practice test

This Web Simulator is for Microsoft data management professionals, data architects, data scientists, and data developers who design big data analytics solutions on Microsoft Azure. Candidates for this exam will have relevant work experience in big data analytics solutions.

Reference: https://www.microsoft.com/en-pk/learning/exam-70-475.aspx

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70-475日本語 exam dumps

70-475 - Designing and Implementing Big Data Analytics Solutions

The 70-475 exam is part of the Azure Big Data Analytics Solutions certification. This exam measures your ability to accomplish the below tasks based on this technology: Big Data Analytics Solutions Please note that this exam on February 2017 was updated.

This certification exam is targeted towards data management professionals, data architects, data scientists, and data developers who design big data analytics solutions on Microsoft Azure. Candidates for this exam will have relevant work experience in big data analytics solutions designing and deployment strategy for an end-to-end solution, This is a list of covered topics:

  • Ingest data for real-time processing
  • Design for data security
  • Deploy con configure SSIS solutions
  • Create and monitor a data factory
  • Implement master data management solutions
  • Design and provision compute clusters
  • Troubleshoot data integration issues
  • Move, transform, and analyze data using MapReduce

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Microsoft 70-475日本語 Exam Syllabus Topics:

SectionObjectives
Design big data analytics solution- Select appropriate big data architecture (batch vs streaming vs hybrid)
- Design data storage strategy using Azure data services
  • 1. Blob storage vs data lake considerations
    • 2. Azure Data Lake Storage concepts
      Develop and optimize data pipelines- Data ingestion and transformation workflows
      - Performance tuning and scaling considerations
      Secure and monitor big data solutions- Monitoring and troubleshooting data pipelines
      - Data security and access control
      Implement data processing solutions- Batch processing with distributed computing
      • 1. Hadoop / HDInsight clusters
        • 2. Apache Spark processing
          - Stream processing implementation
          • 1. Azure Event Hubs ingestion
            • 2. Azure Stream Analytics jobs

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