Try Microsoft : 070-776 valid & accurate questions and answers

Updated: Sep 07, 2026

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Microsoft 070-776 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Engineering Data with Microsoft Cloud Services
Exam Number:70-776
Exam Format:Multiple Response, Scenario-Based Questions, Case Study, Drag and Drop, Build List, Multiple Choice
Available Languages:English
Passing Score:700/1000
Exam Duration:120-150
Related Certifications:MCSA: Data Engineering with Azure
MCSE: Data Management and Analytics
Exam Price:USD 165
Certificate Validity Period:Certification retired; exam retired June 30, 2019
Real Exam Qty:40-60
Sample Questions:Microsoft 070-776 Sample Questions
Exam Way:Pearson VUE testing centers worldwide; retired June 30, 2019.
Pre Condition:No mandatory prerequisite exam. Intended for data engineers, data architects, data scientists, and data developers. Common prerequisites included Azure data services, relational databases, Windows administration, and data analytics experience.
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/

Difficulty in writing MICROSOFT 70-776 Exam

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

Perform Big Data Engineering on Microsoft Cloud Services (beta) 70-776 Dumps Provided Study Notes

Exams-boost expert team recommend you to prepare some notes on these topics along with it don't forget to practice Perform Big Data Engineering on Microsoft Cloud Services (beta) 70-776 Dumps which been written by our expert team.

Both these will help you a lot to clear this exam with good marks.

  • Azure Storage Explorer
  • Azure Data Factory
  • Azure Backup Services
  • Azure Data Factory Pipelines
  • Azure Machine Learning
  • Azure Stream Analytics
  • Azure Event Hubs
  • Azure Data Lake
  • SQL Server Integration Services
  • Azcopy
  • Bulk Copy Program
  • T-SQL/U-SQL
  • Azure Storage
  • Azure Data Warehouse

How to book MICROSOFT 70-776 Certifications Exam?

  • Signup/Login to MICROSOFT account
  • Visit to Microsoft Exam Registration
  • Search for MICROSOFT 70-776 Certifications Exam
  • Select Date and Center of examination and confirm with payment value of 165$

Microsoft 070-776 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Design and Implement Cloud-Based Integration by Using Azure Data Factory15-20%- Move, transform, and analyze data
  • 1. Extend processing with custom activities
  • 2. Copy data between environments
  • 3. Create activity types
  • 4. Move data to and from SQL Data Warehouse
- Orchestrate data processing pipelines
  • 1. Provision and run pipelines
  • 2. Manage dependencies
  • 3. Design end-to-end data flows
  • 4. Design schedules
- Implement datasets and linked services
  • 1. Configure linked services
  • 2. Create datasets
  • 3. Implement availability and policies
- Monitor and manage Azure Data Factory
  • 1. Create alerts
  • 2. Identify failures
  • 3. Use monitoring tools
  • 4. Perform redeployments
Topic 2: Manage and Maintain Azure SQL Data Warehouse, Azure Data Lake, Azure Data Factory, and Azure Stream Analytics20-25%- Design storage solutions for big data
  • 1. Optimize storage performance
  • 2. Migrate data
  • 3. Select storage technologies
  • 4. Integrate cloud and on-premises solutions
- Manage data recovery
  • 1. Backup and recovery
  • 2. Support migration scenarios
  • 3. Implement geo-redundancy
- Monitor and optimize services
  • 1. Implement elastic scaling
  • 2. Monitor workloads
  • 3. Troubleshoot performance
  • 4. Manage concurrency
- Implement authentication, authorization, and auditing
  • 1. Integrate with Azure Active Directory
  • 2. Configure firewalls
  • 3. Implement auditing
  • 4. Secure integrated services
- Provision Azure services
  • 1. Deploy Azure SQL Data Warehouse
  • 2. Deploy Azure Stream Analytics
  • 3. Deploy Azure Data Factory
  • 4. Deploy Azure Data Lake
Topic 3: Design and Implement Analytics by Using Azure Data Lake25-30%- Extract and transform data using U-SQL
  • 1. Use U-SQL data types and expressions
  • 2. Generate output files
  • 3. Manage catalogs and structured data
  • 4. Perform joins and analytical operations
- Integrate Azure Data Lake with other services
  • 1. Integrate with Data Catalog and Event Hubs
  • 2. Integrate with HDInsight
  • 3. Integrate with Azure Data Factory
  • 4. Connect with Azure SQL Data Warehouse
- Ingest data into Azure Data Lake Store
  • 1. Tune performance and diagnostics
  • 2. Implement authentication and access control
  • 3. Create and configure Data Lake Store accounts
  • 4. Copy and secure data
- Extend U-SQL programmability
  • 1. Perform federated queries
  • 2. Implement user-defined functions and operators
  • 3. Integrate Python and R
  • 4. Share code and data assets
- Manage Azure Data Lake Analytics
  • 1. Create and manage analytics accounts
  • 2. Optimize jobs and review historical execution
  • 3. Manage users and data sources
  • 4. Monitor and troubleshoot jobs
Topic 4: Design and Implement Complex Event Processing by Using Azure Stream Analytics15-20%- Ingest data for real-time processing
  • 1. Estimate throughput and latency requirements
  • 2. Select appropriate ingestion technologies
  • 3. Process streaming data sources
  • 4. Design reference data streams
  • 5. Design partitioning schemes
- Implement and manage streaming pipelines
  • 1. Coordinate stream and batch processing
  • 2. Stream data to dashboards
  • 3. Archive streaming data
- Design and implement Azure Stream Analytics
  • 1. Configure thresholds and alerts
  • 2. Support continuous learning scenarios
  • 3. Implement scoring models
  • 4. Integrate Azure Machine Learning
- Query real-time data
  • 1. Guarantee event delivery
  • 2. Use Stream Analytics query language
  • 3. Manage time windows
  • 4. Use built-in functions and data types
Topic 5: Design and Implement Azure SQL Data Warehouse Solutions15-20%- Design tables in Azure SQL Data Warehouse
  • 1. Design columnstore indexes
  • 2. Design table geometry
  • 3. Select distribution methods
  • 4. Minimize data skew
- Query data in Azure SQL Data Warehouse
  • 1. Implement query labels
  • 2. Manage statistics
  • 3. Manage resource classes
  • 4. Monitor query performance
- Integrate Azure SQL Data Warehouse with other services
  • 1. Use PolyBase and data ingestion tools
  • 2. Migrate enterprise data warehouses
  • 3. Import and export data
  • 4. Integrate with Azure Machine Learning

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