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Microsoft 070-475

070-475

Exam Code: 070-475

Exam Name: Design and Implement Big Data Analytics Solutions

Updated: May 28, 2026

Q & A: 122 Questions and Answers

070-475 Free Demo download

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About Microsoft 070-475 Exam

Microsoft 070-475 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Design for batch processing
Topic 2
  • Orchestrate data processing activities in a data-driven workflow
Topic 3
  • Design for real-time processing
Topic 4
  • Design a deployme
Topic 5
  • Design and provision compute resources
Topic 6
  • Design for data security

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

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.

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Our 70-475 exam dumps will include those topics:

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

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

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:

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

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