This paper discusses the implementation of cloud computing technology using data mining algorithms. It explores the benefits of distributed computing and MapReduce parallel processing architecture for association rule mining. The paper also introduces Aneka Cloud Strategy and Mahout open source project for data mining parallelism. The theoretical analysis of association rule mining in cloud is also presented.

Discover cloud computing with data mining algorithms, distributed computing, MapReduce, Aneka Cloud Strategy, and Mahout open source project.

Cloud Computing and Data Mining: Implementation with Algorithms

Implementation of Cloud Computing Technology using Data Mining Algorithms

This article discusses cloud implementation for Desklib, including the development and implementation process, migration of data, and roadmap documentation. It provides step-by-step instructions for creating a virtual machine with Microsoft Azure and migrating data to the cloud. The article also covers the benefits of cloud computing and its impact on enterprise technology strategy.

Web Development

Cloud Implementation: Development, Migration, and Roadmap Documentation

History 

This report discusses the outcome, performance, benefits, and limitations of a cloud computing project. It also covers the project team and lessons learned. The report highlights the advantages of cloud computing, such as cost savings, backup and recovery management, and optimized server capacity. However, it also mentions the limitations, such as internet dependence, data incompatibility, and security risks. Subject: Cloud Computing. Course Code: N/A. Course Name: N/A. College/University: N/A.

Implementation of Cloud Computing Technology using Data Mining Algorithms

Cloud Implementation: Development, Migration, and Roadmap Documentationlg...

Cloud Computing Technology Project Closure Reportlg...

Cloud Implementation: Development, Migration, and Roadmap Documentation

Cloud Computing Technology Project Closure Report