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MICROSOFT 70-775 Exam Reference, Microsoft Documents

Overview about MICROSOFT 70-775 Exam

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

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

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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:

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