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Microsoft 070-775 certification exam is designed to test candidates on their ability to perform data engineering on Microsoft Azure HDInsight. HDInsight is a cloud-based service that allows users to process and analyze large amounts of data using popular open-source technologies, such as Hadoop, Spark, and Hive. 070-775 exam is intended for data engineers, data architects, and other IT professionals who work with big data solutions.

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Microsoft 070-775 certification exam is a great way to demonstrate your expertise in big data engineering on Azure HDInsight. It covers a wide range of topics and requires a good understanding of tools like Hive, Pig, and Spark, as well as Azure Data Factory, Azure Stream Analytics, and Azure Databricks. Passing the exam leads to a Microsoft Certified: Azure Data Engineer Associate certification, which is highly valued in the industry and can help you advance your career.

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

The Microsoft 070-775 exam measures your knowledge of managing big data clusters and data pipelines on Azure HDInsight. You will be tested on topics such as data ingestion, data processing, data transformation, data storage, and data analysis using Azure HDInsight. 070-775 exam will also test your skills in implementing advanced analytics solutions using Azure HDInsight.

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Microsoft 070-775 Exam Syllabus Topics:

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

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