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  2. Cloud computing - Wikipedia

    en.wikipedia.org/wiki/Cloud_computing

    Hybrid cloud adoption depends on a number of factors such as data security and compliance requirements, level of control needed over data, and the applications an organization uses. [ 66 ] Another example of hybrid cloud is one where IT organizations use public cloud computing resources to meet temporary capacity needs that can not be met by ...

  3. Cloud computing security - Wikipedia

    en.wikipedia.org/wiki/Cloud_computing_security

    Cloud computing and storage provide users with the capabilities to store and process their data in third-party data centers. [1] Organizations use the cloud in a variety of different service models (with acronyms such as SaaS, PaaS, and IaaS) and deployment models (private, public, hybrid, and community).

  4. HP CloudSystem - Wikipedia

    en.wikipedia.org/wiki/HP_CloudSystem

    The migration of traditional IT, in which IT directly controls IT purchasing, deployment, management, and use, to a cloud computing model holds a number of challenges. A paper titled "Cloud Migration: A Case Study of Migrating an Enterprise IT System to IaaS," by researchers at the Cloud Computing Co-laboratory, School of Computer Science, University of St Andrews, raises several socio ...

  5. Distributed file system for cloud - Wikipedia

    en.wikipedia.org/wiki/Distributed_file_system...

    Modern data centers must support large, heterogenous environments, consisting of large numbers of computers of varying capacities. Cloud computing coordinates the operation of all such systems, with techniques such as data center networking (DCN), the MapReduce framework, which supports data-intensive computing applications in parallel and distributed systems, and virtualization techniques ...

  6. Data migration - Wikipedia

    en.wikipedia.org/wiki/Data_migration

    Post-migration: After data migration, results are subjected to data verification to determine whether data was accurately translated, is complete, and supports processes in the new system. During verification, there may be a need for a parallel run of both systems to identify areas of disparity and forestall erroneous data loss .

  7. Data virtualization - Wikipedia

    en.wikipedia.org/wiki/Data_virtualization

    Data virtualization is an approach to data management that allows an application to retrieve and manipulate data without requiring technical details about the data, such as how it is formatted at source, or where it is physically located, [1] and can provide a single customer view (or single view of any other entity) of the overall data.

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