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Exam Code: 070-475
Exam Name: Design and Implement Big Data Analytics Solutions
Updated: Sep 27, 2026
Q & A: 122 Questions and Answers
070-475 Free Demo download
Microsoft 070-475 is a certification exam that is designed to assess an individual’s ability to design and implement big data analytics solutions. 070-475 exam is intended for IT professionals who are responsible for designing and implementing big data solutions using Microsoft technologies. 070-475 exam is part of the Microsoft Certified Solutions Expert (MCSE) certification program, and passing 070-475 exam will help you earn the MCSE: Data Management and Analytics certification.
Reference: https://www.microsoft.com/en-pk/learning/exam-70-475.aspx
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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.
To prepare for the exam, candidates should have a good understanding of big data technologies, Azure services, and machine learning concepts. They should also have hands-on experience working with these technologies. Microsoft offers a range of training courses and study materials to help candidates prepare for the exam, including online training courses, study guides, and practice exams.
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| Section | Weight | Objectives |
|---|---|---|
| Design Big Data Real-Time Processing Solutions | 25-30% | - Design for real-time processing - Design for Lambda architecture - Design and provision compute resources - Ingest data for real-time processing |
| Operationalize End-to-End Cloud Analytics Solutions | 25-30% | - Create and configure Azure Data Factory - Monitor and manage data pipelines - Design deployment strategies - Move, transform, and analyze data - Orchestrate data processing workflows |
| Design Big Data Batch Processing and Interactive Solutions | 20-25% | - Ingest data for batch and interactive processing - Design interactive queries for big data - Design for batch processing - Design for data security - Design and provision compute clusters |
| Design Machine Learning Solutions | 25-30% | - Create and manage experiments - Apply custom processing with R and Python - Determine pre-processing and training locations - Select input/output data types - Publish machine learning web services |
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