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Reference: https://www.microsoft.com/en-us/learning/exam-70-776.aspx
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Overview about MICROSOFT 70-776 Exam
- Number of Questions: 40-60
- Format: Multiple choice, multiple answer
- Passing Score: 70-80%
- Registration Fee: 165 USD
- Length of Examination: 120 minutes
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Perform Big Data Engineering on Microsoft Cloud Services 70-776 Exam
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.
This is the list of the contents in our Perform Big Data Engineering on Microsoft Cloud Services 70-776 Practice Test:
- Backup and Recovery Service Plan for Azure Storage
- migrate from an on-premises data warehouse to Azure SQL Data Warehouse
- Cloud based integration using Azure Data Factory.
- Design Storage Solutions
- Provision Azure SQL Data Warehouse, Azure Data Lake, Azure Data Factory, and Azure Stream Analytics
- Azure Data Factory Pipelines.
- Monitor Azure SQL Data Warehouse, Azure Data Lake, and Azure Stream Analytics