Difference between revisions of "Training:SummerSchool2018:Programme:Cloud"
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'''Abstract''': In this seminar, you will learn about Cloud Computing, the 5th internet revolution, that made it possible to analyze Big Data by providing elastic resource management to accommodate the application's processing needs. Then, you will be introduced to the MapReduce programming paradigm that allows developing parallelized programs using very simple syntax. Finally, you will develop a simple Hadoop application on Microsoft's Azure Cloud. | '''Abstract''': In this seminar, you will learn about Cloud Computing, the 5th internet revolution, that made it possible to analyze Big Data by providing elastic resource management to accommodate the application's processing needs. Then, you will be introduced to the MapReduce programming paradigm that allows developing parallelized programs using very simple syntax. Finally, you will develop a simple Hadoop application on Microsoft's Azure Cloud. | ||
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| + | '''Instructor''': Shadi Khalifa, ''Cognitive Analytics Development Hub, Centre for Advanced Computing, Queen’s University'' | ||
* Please note that the aforementioned technologies are useful for Big Data applications but not as useful for computational intensive applications. | * Please note that the aforementioned technologies are useful for Big Data applications but not as useful for computational intensive applications. | ||
Latest revision as of 17:53, 18 June 2018
Cloud Computing and MapReduce
Abstract: In this seminar, you will learn about Cloud Computing, the 5th internet revolution, that made it possible to analyze Big Data by providing elastic resource management to accommodate the application's processing needs. Then, you will be introduced to the MapReduce programming paradigm that allows developing parallelized programs using very simple syntax. Finally, you will develop a simple Hadoop application on Microsoft's Azure Cloud.
Instructor: Shadi Khalifa, Cognitive Analytics Development Hub, Centre for Advanced Computing, Queen’s University
- Please note that the aforementioned technologies are useful for Big Data applications but not as useful for computational intensive applications.
