Hadoop and Azure HDInsight Practice Exam

Hadoop and Azure HDInsight Practice Exam

Hadoop is a popular open-source framework that helps organizations process and store very large amounts of data across multiple computers. It is designed to handle “big data” in a cost-effective and reliable way. On the other hand, Azure HDInsight is Microsoft’s cloud-based service that brings Hadoop and other big data technologies to the cloud, making it easier for companies to scale data processing without setting up their own infrastructure.

Together, Hadoop and Azure HDInsight allow businesses to manage, analyze, and gain insights from massive datasets. This certification helps learners understand both the basics of Hadoop and how it works in the Azure environment, preparing them to work with modern data-driven systems.

Who should take the Exam?

This exam is ideal for:

• Students & Graduates
• Data Analysts
• Data Engineers
• IT Professionals
• Business Intelligence Specialists
• Developers

Skills Required

• Basic understanding of databases and data concepts.
• Familiarity with cloud platforms (helpful but not mandatory).
• Logical problem-solving and analytical skills.
• Interest in working with large-scale data processing.

Knowledge Gained

• Fundamentals of Hadoop and distributed data processing.
• Hands-on use of Azure HDInsight services.
• Working with big data tools like Hive, Spark, and HBase in Azure.
• Designing and running data workflows in the cloud.
• Practical skills in storing, processing, and analyzing data at scale.

Course Outline

The Hadoop and Azure HDInsight Exam covers the following topics -

1. Introduction to Big Data and Hadoop

• What is big data?
• Hadoop ecosystem overview
• Importance of distributed computing

2. Core Components of Hadoop

• Hadoop Distributed File System (HDFS)
• MapReduce basics
• YARN and resource management

3. Introduction to Azure HDInsight

• What is HDInsight?
• Benefits of managed Hadoop services
• Comparing on-premise Hadoop vs. HDInsight

4. Working with HDInsight Clusters

• Setting up clusters on Azure
• Cluster types (Hadoop, Spark, Hive, Kafka, etc.)
• Managing cluster resources

5. Data Processing with Hive and Spark

• HiveQL basics
• Using Spark for big data analytics
• Integrating data sources with HDInsight

6. Security and Monitoring

• Securing data on HDInsight
• Role-based access control
• Monitoring and troubleshooting clusters

7. Integration with Azure Services

• HDInsight with Azure Data Lake
• Integration with Azure Synapse and Power BI
• Real-time data pipelines with Azure Event Hubs