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Microsoft 070-775 Valid Braindumps - Perform Data Engineering on Microsoft Azure HDInsight

070-775
  • Exam Code: 070-775
  • Exam Name: Perform Data Engineering on Microsoft Azure HDInsight
  • Updated: Sep 15, 2026
  • Q & A: 63 Questions and Answers
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About Microsoft 070-775 Exam

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How to book MICROSOFT 70-775 Certifications Exam?

  • Visit to Microsoft Exam Registration
  • Signup/Login to MICROSOFT account
  • Search for MICROSOFT 70-775 Certifications Exam
  • Select Date and Center of examination and confirm with payment value of 165$

Overview about MICROSOFT 70-775 Exam

  • Registration Fee: 165 USD
  • Format: Multiple choice, multiple answer
  • Length of Examination: 120 minutes
  • Passing Score: 70-80%
  • Number of Questions: 40-60

Perform Data Engineering on Microsoft Azure HDInsight 70-775 Exam

Perform Data Engineering on Microsoft Azure HDInsight 70-775 Exam is centered around Big Data Analytic framework which is one of the hottest topics and technology areas in the industry. Azure HDInsight is one of the services within the Microsoft Azure platform that services the ability to build scalable, Big Data solutions in the cloud. In an effort to expand out the breadth of certifications and exams offered around Microsoft Azure, the cloud, and Big Data, Microsoft has added the Perform Data Engineering on Microsoft Azure HDInsight 70-775 Exam.

This certification exam is targeted towards data engineers, data architects, data scientists, and data developers who implement big data engineering workflows on HDInsight. Candidates for this exam should have relevant work experience in big data analytics solutions. Candidates should also be familiar with the features and capabilities of batch data processing, real-time processing, and interactive processing. Candidates who take this exam are expected to be able to apply the Microsoft cloud ecosystem to design and implement big data engineering workflows and to use open source technologies for strategic value-add. 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 Data Engineering on Microsoft Azure HDInsight 70-775 Exam Practice Test Paper and Dumps will provide you 100% confidence to make you appear for Microsoft 70-775 Exam.

This is the list of the contents in our Perform Data Engineering on Microsoft Azure HDInsight 70-775 Practice Test:

  • Operationalize Hadoop and Spark
  • Spark streaming applications using DStream API
  • Configure HDInsight clusters
  • Build Solution that use Hbase
  • Data analysis using Hive
  • Data analysis using Spark SQL
  • Design batch ETL solutions for big data with Spark
  • Build solutions that use Kafka

Reference: https://www.microsoft.com/en-us/learning/exam-70-775.aspx

For more info visit:

MICROSOFT 70-775 Exam Reference, Microsoft Documents

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Microsoft 070-775 Exam Syllabus Topics:

SectionWeightObjectives
Implement Big Data Real-Time Processing Solutions20%- Develop Spark Streaming applications
  • 1. Use DStream and Structured Streaming
    - Integrate with Kafka, Storm and HBase
    • 1. Build end-to-end real-time pipelines
      Implement Big Data Batch Processing Solutions30%- Use Apache Hive and Pig
      • 1. Optimize Hive queries
        • 2. Design and execute batch ETL
          - Work with Apache Spark
          • 1. Develop batch applications
            • 2. Operationalize Spark jobs
              Implement Big Data Interactive Processing Solutions20%- Query data with Spark SQL and Interactive Hive
              • 1. Use notebooks: Jupyter, Zeppelin
                • 2. Perform exploratory analysis
                  - Access data with Apache Phoenix on HBase
                  Administer and Provision HDInsight Clusters30%- Deploy and configure HDInsight clusters
                  • 1. Secure clusters and manage access
                    • 2. Configure storage and networking
                      • 3. Choose cluster types and sizes
                        - Ingest and manage data
                        • 1. Import data from various sources
                          • 2. Monitor and debug jobs
                            • 3. Scale and maintain clusters

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