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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 batch processing and interactive solutions (30-35%)
- Design big data real-time processing solutions (30-35%)
For more info visit: Microsoft Official 70-475 Exam Reference
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:
- Troubleshoot data integration issues
- 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
- Deploy con configure SSIS solutions
- Ingest data for real-time processing
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Microsoft 70-475日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Operationalize End-to-End Cloud Analytics Solutions | 25-30% | - Move, transform, and analyze data - Design deployment strategies - Orchestrate data processing workflows - Create and configure Azure Data Factory - Monitor and manage data pipelines |
| Design Big Data Real-Time Processing Solutions | 25-30% | - Design and provision compute resources - Design for real-time processing - Design for Lambda architecture - Ingest data for real-time processing |
| Design Big Data Batch Processing and Interactive Solutions | 20-25% | - Design for batch processing - Design for data security - Design interactive queries for big data - Design and provision compute clusters - Ingest data for batch and interactive processing |
| Design Machine Learning Solutions | 25-30% | - Select input/output data types - Determine pre-processing and training locations - Publish machine learning web services - Create and manage experiments - Apply custom processing with R and Python |
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