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Microsoft 070-475 certification exam is designed to test the skills and knowledge of professionals in the field of big data analytics. Design and Implement Big Data Analytics Solutions certification is intended for individuals who are responsible for designing and implementing big data analytics solutions for organizations. 70-475 exam focuses on topics such as data processing, data storage, data analysis, and data visualization.
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Microsoft 070-475, also known as the Design and Implement Big Data Analytics Solutions Certification Exam, is a certification test designed for individuals who are interested in building big data analytics solutions using Microsoft technologies. 70-475 exam is aimed at professionals who work with data systems, data warehousing, data analysis, and data integration.
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Microsoft 070-475 certification exam is designed for professionals who have experience in designing and implementing big data solutions using Microsoft Azure technologies. 70-475 exam is part of the Microsoft Certified Solutions Expert (MCSE) certification track and aims to validate the skills and knowledge required to design and implement big data analytics solutions that leverage the power of Azure technologies.
To take the Microsoft 070-475 exam, candidates must have a strong understanding of various big data technologies, such as Hadoop, Spark, and Azure Data Lake Analytics. They should also have experience working with SQL Server Integration Services (SSIS), SQL Server Analysis Services (SSAS), and SQL Server Reporting Services (SSRS). Additionally, candidates should have experience working with cloud-based data solutions, such as Azure Data Factory and Azure HDInsight.
Reference: https://www.microsoft.com/en-pk/learning/exam-70-475.aspx
Microsoft 70-475 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Implement data processing solutions | - Stream processing implementation
|
| Secure and monitor big data solutions | - Monitoring and troubleshooting data pipelines - Data security and access control |
| Develop and optimize data pipelines | - Data ingestion and transformation workflows - Performance tuning and scaling considerations |
| Design big data analytics solution | - Design data storage strategy using Azure data services
|
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