Microsoft 070-475日本語 dumps - in .pdf

070-475日本語 pdf
  • Exam Code: 070-475日本語
  • Exam Name: Design and Implement Big Data Analytics Solutions (070-475日本語版)
  • Updated: Sep 03, 2026
  • Q & A: 122 Questions and Answers
  • PDF Price: $59.99
  • Free Demo

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  • Exam Code: 070-475日本語
  • Exam Name: Design and Implement Big Data Analytics Solutions (070-475日本語版)
  • Updated: Sep 03, 2026
  • Q & A: 122 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $119.98  $79.99
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Microsoft 070-475日本語 dumps - Testing Engine

070-475日本語 Testing Engine
  • Exam Code: 070-475日本語
  • Exam Name: Design and Implement Big Data Analytics Solutions (070-475日本語版)
  • Updated: Sep 03, 2026
  • Q & A: 122 Questions and Answers
  • Software Price: $59.99
  • Testing Engine

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Microsoft 070-475日本語 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Design and provision compute clusters
Topic 2
  • Design for data security
Topic 3
  • Orchestrate data processing activities in a data-driven workflow
Topic 4
  • Design for real-time processing

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

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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:

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

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