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
- Ingest data for real-time processing
- Design and provision compute clusters
- Move, transform, and analyze data using MapReduce
- Create and monitor a data factory
- Implement master data management solutions
- Deploy con configure SSIS solutions
- Design for data security
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.
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Microsoft 070-475 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Design Big Data Real-Time Processing Solutions | 25-30% | - Ingest data for real-time processing - Design for real-time processing - Design for Lambda architecture - Design and provision compute resources |
| Design Big Data Batch Processing and Interactive Solutions | 20-25% | - Design interactive queries for big data - Design for batch processing - Design and provision compute clusters - Ingest data for batch and interactive processing - Design for data security |
| 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 |
| Operationalize End-to-End Cloud Analytics Solutions | 25-30% | - Create and configure Azure Data Factory - Orchestrate data processing workflows - Design deployment strategies - Move, transform, and analyze data - Monitor and manage data pipelines |
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