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Microsoft 070-475 certification exam is designed for professionals who are interested in validating their skills and knowledge in designing and implementing big data analytics solutions. Design and Implement Big Data Analytics Solutions certification exam covers a wide range of topics such as data analysis, data storage, data processing, and data visualization. Candidates who pass 070-475 exam will demonstrate their ability to design and implement big data analytics solutions that meet the needs of their organizations.
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In 070-475 exam, the candidates are required to demonstrate their knowledge and skills in various areas of big data analytics, such as designing and implementing big data solutions, implementing security and compliance, and managing and maintaining big data solutions. 070-475 exam also covers topics such as data analysis and visualization, data integration, data processing, and data storage. The candidates are expected to have a good understanding of a variety of big data technologies, including Hadoop, Spark, HBase, and Hive. Additionally, they should also be familiar with various data analytics tools and techniques, such as Power BI and R.
Reference: https://www.microsoft.com/en-pk/learning/exam-70-475.aspx
Microsoft 070-475 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Operationalize End-to-End Cloud Analytics Solutions | 25-30% | - Move, transform, and analyze data - Monitor and manage data pipelines - Design deployment strategies - Orchestrate data processing workflows - Create and configure Azure Data Factory |
| Topic 2: Design Big Data Batch Processing and Interactive Solutions | 20-25% | - Design for data security - Design and provision compute clusters - Design interactive queries for big data - Ingest data for batch and interactive processing - Design for batch processing |
| Topic 3: Design Machine Learning Solutions | 25-30% | - Determine pre-processing and training locations - Publish machine learning web services - Select input/output data types - Create and manage experiments - Apply custom processing with R and Python |
| Topic 4: Design Big Data Real-Time Processing Solutions | 25-30% | - Design and provision compute resources - Ingest data for real-time processing - Design for real-time processing - Design for Lambda architecture |
