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  • Number of Questions: 40-60
  • Length of Examination: 120 minutes
  • Format: Multiple choice, multiple answer
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Reference: https://www.microsoft.com/en-us/learning/exam-70-775.aspx

Microsoft 070-775 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Implement Big Data Interactive Processing Solutions25%- Implement interactive processing on HBase
  • 1. Use Apache Phoenix
  • 2. Query HBase data efficiently
- Create interactive query solutions
  • 1. Use Interactive Hive
  • 2. Use Spark SQL
- Perform exploratory data analysis
  • 1. Analyze data with Spark SQL
  • 2. Work with Jupyter notebooks
  • 3. Use Apache Zeppelin
  • 4. Use Hive for exploration
Topic 2: Implement Big Data Batch Processing Solutions25%- Operationalize Hadoop and Spark workloads
  • 1. Automate workflows with Apache Oozie
  • 2. Use Azure Data Factory orchestration
- Design ETL solutions with Spark
  • 1. Create Spark ETL processes
  • 2. Optimize Spark performance
  • 3. Process large-scale datasets
- Implement batch processing with Hive and Pig
  • 1. Manage data processing workflows
  • 2. Design Hive-based solutions
  • 3. Execute Pig jobs
Topic 3: Administer and Provision HDInsight Clusters25%- Ingest and prepare data
  • 1. Optimize data storage formats
  • 2. Load data into Azure Blob Storage
  • 3. Load data into Azure Data Lake Store
- Monitor and troubleshoot clusters
  • 1. Analyze HDInsight logs
  • 2. Monitor resources with Operations Management Suite
  • 3. Use YARN logs and heap dumps
- Deploy and configure HDInsight clusters
  • 1. Create and manage HDInsight cluster types
  • 2. Customize clusters with script actions
  • 3. Configure storage and networking
- Secure and manage multi-user clusters
  • 1. Manage user authorization and permissions
  • 2. Configure domain-joined clusters
  • 3. Use Ambari and Ranger administration tools
Topic 4: Implement Big Data Real-Time Processing Solutions25%- Implement event processing solutions
  • 1. Store and process streaming data with HBase
  • 2. Integrate Apache Kafka
  • 3. Use Apache Storm
- Create Spark Streaming applications
  • 1. Process streaming data in real time
  • 2. Implement Structured Streaming
  • 3. Use DStreams

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