Real Microsoft 70-776 practice exam questions for easy pass!
Last Updated: Sep 01, 2026
No. of Questions: 92 Questions & Answers with Testing Engine
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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
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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.
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| Section | Weight | Objectives |
|---|---|---|
| Manage and Maintain Azure SQL Data Warehouse, Azure Data Lake, Azure Data Factory, and Azure Stream Analytics | 20-25% | - Provision Azure services
|
| Design and Implement Azure SQL Data Warehouse Solutions | 15-20% | - Design tables in Azure SQL Data Warehouse
|
| Design and Implement Cloud-Based Integration by Using Azure Data Factory | 15-20% | - Monitor and manage Azure Data Factory
|
| Design and Implement Analytics by Using Azure Data Lake | 25-30% | - Integrate Azure Data Lake with other services
|
| Design and Implement Complex Event Processing by Using Azure Stream Analytics | 15-20% | - Ingest data for real-time processing
|
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