Microsoft 70-475 Q&A - in .pdf

  • Exam Code: 70-475
  • Exam Name: Design and Implement Big Data Analytics Solutions
  • Q & A: 122 Questions and Answers
  • PDF Price: $49.99
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Microsoft 70-475 Q&A - Testing Engine

  • Exam Code: 70-475
  • Exam Name: Design and Implement Big Data Analytics Solutions
  • Q & A: 122 Questions and Answers
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To take the Microsoft 070-475 exam, candidates should have experience designing and implementing big data solutions using Microsoft technologies. They should also have experience working with Microsoft Azure and be familiar with Microsoft Power BI. Candidates should also have a deep understanding of big data analytics technologies and be able to apply this knowledge to design and implement effective big data solutions.

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Candidates who pass the Microsoft 070-475 certification exam will be recognized as experts in designing and implementing big data solutions. Design and Implement Big Data Analytics Solutions certification is highly regarded in the industry and can help professionals advance their careers. Successful candidates will also have the skills necessary to use Microsoft Azure services to implement big data solutions that are scalable, efficient, and cost-effective. Overall, the 070-475 certification exam is an excellent choice for professionals who want to specialize in big data analytics solutions.

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

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Microsoft 70-475 Exam Syllabus Topics:

SectionObjectives
Topic 1: Implement data processing solutions- Stream processing implementation
  • 1. Azure Event Hubs ingestion
    • 2. Azure Stream Analytics jobs
      - Batch processing with distributed computing
      • 1. Apache Spark processing
        • 2. Hadoop / HDInsight clusters
          Topic 2: 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
              Topic 3: Develop and optimize data pipelines- Data ingestion and transformation workflows
              - Performance tuning and scaling considerations
              Topic 4: Secure and monitor big data solutions- Data security and access control
              - Monitoring and troubleshooting data pipelines

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