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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
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
- Ingest data for real-time processing
- Implement master data management solutions
- Design for data security
- Move, transform, and analyze data using MapReduce
- Create and monitor a data factory
- Design and provision compute clusters
- Troubleshoot data integration issues
Reference: https://www.microsoft.com/en-pk/learning/exam-70-475.aspx
Microsoft 70-475日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Operationalize End-to-End Cloud Analytics Solutions | 25-30% | - Design deployment strategies - Monitor and manage data pipelines - Create and configure Azure Data Factory - Orchestrate data processing workflows - Move, transform, and analyze data |
| Design Big Data Real-Time Processing Solutions | 25-30% | - Design for real-time processing - Design and provision compute resources - Design for Lambda architecture - Ingest data for real-time processing |
| Design Big Data Batch Processing and Interactive Solutions | 20-25% | - Design for data security - Ingest data for batch and interactive processing - Design and provision compute clusters - Design for batch processing - Design interactive queries for big data |
| Design Machine Learning Solutions | 25-30% | - Determine pre-processing and training locations - Select input/output data types - Publish machine learning web services - Apply custom processing with R and Python - Create and manage experiments |







