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Perform Big Data Engineering on Microsoft Cloud Services 70-776 Exam is intended mainly to design analytical solutions and build operational solutions on Azure. Candidates for this exam have relevant work experience in data engineering issues with Azure SQL Data Warehouse, Azure Data Lake, Azure Data Factory, and Azure Stream Analytics. Candidates are familiar with the features and capabilities of batch data processing, real-time processing, and operationalization technologies.
Candidates for this exam can apply the Microsoft cloud ecosystem to designs and can implement big data analytics solutions to meet their project's needs. In an effort to expand out the breadth of certifications and exams offered around Microsoft Azure and the cloud, Microsoft has added the Perform Big Data Engineering on Microsoft Cloud Services 70-776 Exam. This exam only available for the candidates till 30th June 2019 after that this may get replace with some other exam so you can plan get it completed before it get expire.
We think our Perform Big Data Engineering on Microsoft Cloud Services (beta) 70-776 Exam Practice Test Paper and Dumps will provide you 100% confidence to make you appear for MICROSOFT 70-776 Exam.
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It is one of the toughest exam and it requires you a lot of hands-on experience. It is advisable to have prior knowledge of Big Data analytics on Microsoft. The more experience you have, the more it is beneficial for you, Major challenging things which you can find in exam is about different scenario based questions, you must have strong understanding of Big Data, Machine Learning, Data Science, Data Analytics.
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Reference: https://www.microsoft.com/en-us/learning/exam-70-776.aspx
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Design and Implement Complex Event Processing by Using Azure Stream Analytics | 15-20% | - Design and implement Azure Stream Analytics
|
| Topic 2: Design and Implement Analytics by Using Azure Data Lake | 25-30% | - Extend U-SQL programmability
|
| Topic 3: Design and Implement Cloud-Based Integration by Using Azure Data Factory | 15-20% | - Monitor and manage Azure Data Factory
|
| Topic 4: Manage and Maintain Azure SQL Data Warehouse, Azure Data Lake, Azure Data Factory, and Azure Stream Analytics | 20-25% | - Design storage solutions for big data
|
| Topic 5: Design and Implement Azure SQL Data Warehouse Solutions | 15-20% | - Design tables in Azure SQL Data Warehouse
|
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