This course provides an introduction to the Hadoop platform and application framework, giving novice programmers and business people the opportunity to learn the core tools used to wrangle and analyze big data. Through hands-on examples with Hadoop and Spark frameworks, participants will gain an understanding of the Hadoop architecture, software stack, and execution environment, as well as the concepts and techniques such as Map-Reduce used to solve big data problems.
Hadoop Tutorials for Beginners
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This Hadoop Tutorials for Beginners course provides an introduction to Big Data and covers topics such as HDFS Architecture, MapReduce, Hive, Pig, Spark, NoSQL, HBase, Sqoop, Flume, and Kafka. It is designed to help beginners understand the basics of Big Data and how to use Hadoop to process and analyze it. The course is comprehensive and provides detailed explanations of each topic, making it an ideal resource for anyone looking to learn more about Big Data and Hadoop.
Hadoop Tutorials
2.5
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This course provides an introduction to Hadoop, a powerful open-source framework for distributed storage and processing of large datasets. It covers topics such as HDFS features, architecture, high availability, fault tolerance, secondary name node, and installation. It is a great resource for those looking to learn more about Hadoop and its capabilities.
Big Data Use Cases - Bank Data Analysis Using Hadoop
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This Big Data Use Case study explores how Hadoop can be used to analyze banking data. It covers two main topics: data integration and table creation, and content analysis and archival. The study provides a comprehensive overview of how Hadoop can be used to analyze banking data, from data integration to archival. It is a valuable resource for anyone looking to use Hadoop for banking data analysis.
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