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

70-475日本語 real exams

Exam Code: 70-475J

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

Updated: Jul 20, 2026

Q & A: 122 Questions and Answers

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Our 70-475 exam dumps will include those topics:

  • Design big data batch processing and interactive solutions (30-35%)
  • Operationalize end-to-end cloud analytics solutions (30-35%)
  • Design big data real-time processing solutions (30-35%)

For more info visit: Microsoft Official 70-475 Exam Reference

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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:

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

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

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Microsoft 70-475日本語 Exam Syllabus Topics:

SectionObjectives
Topic 1: Implement data processing solutions- Batch processing with distributed computing
  • 1. Hadoop / HDInsight clusters
    • 2. Apache Spark processing
      - Stream processing implementation
      • 1. Azure Stream Analytics jobs
        • 2. Azure Event Hubs ingestion
          Topic 2: Develop and optimize data pipelines- Data ingestion and transformation workflows
          - Performance tuning and scaling considerations
          Topic 3: Design big data analytics solution- Design data storage strategy using Azure data services
          • 1. Blob storage vs data lake considerations
            • 2. Azure Data Lake Storage concepts
              - Select appropriate big data architecture (batch vs streaming vs hybrid)
              Topic 4: Secure and monitor big data solutions- Data security and access control
              - Monitoring and troubleshooting data pipelines

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