Data-intensive computing this approach is considered suitable for data-intensive computing and problems which are “embarrassingly parallel”, i.e. where it is relatively easy to separate the problem into a number of parallel tasks and there is no dependency or communication required between the tasks other than overall management of the tasks. These types of data processing problems are inherently adaptable to various forms of distributed computing including clusters, data grids, and cloud computing. Several common characteristics of data-intensive computing systems distinguish them from other forms of computing: A variety of system architectures have been implemented for data-intensive computing and large-scale data analysis applications
Home server computer, or a plug computer; pre-configured commercial home server appliances are also available. An uninterruptible power supply is sometimes used in case of power outages that can possibly corrupt data. Home servers often run headless, and can be administered remotely through a command shell, or graphically through a remote desktop system such as RDP, VNC, Webmin, Apple Remote Desktop, or many others. Some home server operating systems (such as Windows Home Server) include a consumer-focused graphical user interface (GUI) for setup and configuration that is available on home computers on the home network (and remotely over the Internet via remote