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Big Data Hadoop

Track :

Programming

Lessons no : 84

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What will you learn in this course?
  • Master how to set up and configure Hadoop clusters for scalable big data storage and processing
  • Analyze large datasets using Hadoop MapReduce for efficient data analysis and transformation
  • Implement data ingestion and integration techniques with Hadoop ecosystem tools like HDFS and Hive
  • Optimize Hadoop performance through tuning, resource management, and job scheduling strategies
  • Develop data processing workflows using Hadoop ecosystem components such as Pig, Flink, and Spark
  • Ensure data security and compliance within Hadoop environments through best practices and security protocols
  • Troubleshoot common Hadoop issues related to cluster management, data integrity, and job failures
  • Design and deploy data pipelines for real-time and batch processing using Hadoop frameworks
  • Apply data analytics and visualization techniques to interpret big data insights effectively
  • Utilize Hadoop ecosystem tools for data warehousing, querying, and reporting purposes
  • Implement data governance and metadata management within Hadoop infrastructure
  • Leverage Hadoop for machine learning and AI applications on large-scale datasets
  • Understand the architecture and components of Hadoop to facilitate system design and integration
  • Evaluate and select appropriate Hadoop tools and technologies for specific big data projects

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Lessons | 84
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Hadoop is an open-source software framework for storing data and running applications on clusters of commodity hardware. It provides massive storage for any kind of data, enormous processing power and the ability to handle virtually limitless concurrent tasks or jobs.