cloud portability : The ability of a cloud computing product, solution or service to be migrated to a new vendor or location without incurring substantial porting and integration issues.
(†2596)
cloud portability : Cloud portability is applicable to all service models of cloud computing - SaaS, PaaS, IaaS and hybrid - regardless of whether they are public or private. However, most cloud portability scenarios occur in public-to-public or public-to-private cloud transfer.
¶ Cloud portability depends on the level of interoperability a cloud service or vendor provides in their offerings. A cloud solution built on non-proprietary and open standards is most likely to be easily portable among any similar cloud vendors or architecture. OpenStack and CloudStack are among the initiatives that fosters cloud solutions, which are highly interoperable among supporting vendors. (†2597)
cloud provider (s.v. "cloud provider"): A cloud provider is a company that delivers cloud computing based services and solutions to businesses and/or individuals. This service organization may provide rented and provider-managed virtual hardware, software, infrastructure and other related services. Cloud services are becoming increasingly desirable for companies because they offer advantages in terms of cost, scalability and accessibility.
¶ A cloud provider is also known as a utility computing provider. This role is typically related to that of a managed service provider (MSP), but usually, the latter provides other managed IT solutions.
¶
Cloud providers are generally organizations that provide some form of IT infrastructure that is commercially distributed and sourced across several subscribers - typically businesses. Cloud providers deliver cloud solutions through on-demand, pay-as-you-go systems as a service to customers and end users. Cloud provider customers access cloud resources through Internet and programmatic access and are only billed for resources and services used according to a subscribed billing method.
(†505)
dark data (s.v. "dark data"): Dark data is a type of unstructured, untagged and untapped data that is found in data repositories and has not been analyzed or processed. It is similar to big data but differs in how it is mostly neglected by business and IT administrators in terms of its value.
¶ Dark data is also known as dusty data.
¶ Dark data is data that is found in log files and data archives stored within large enterprise class data storage locations. It includes all data objects and types that have yet to be analyzed for any business or competitive intelligence or aid in business decision making. Typically, dark data is complex to analyze and stored in locations where analysis is difficult. The overall process can be costly. It also can include data objects that have not been seized by the enterprise or data that are external to the organization, such as data stored by partners or customers.
¶ IDC, a research firm, stated that up to 90 percent of big data is dark data. (†2703)
data exhaust (s.v. "data exhaust"): the data generated as trails or information byproducts resulting from all digital or online activities. These consist of storable choices, actions and preferences such as log files, cookies, temporary files and even information that is generated for every process or transaction done digitally. This data can be very revealing about an individual, so it is very valuable to researchers and especially to marketers and business entities.
¶ Data exhaust refers to all of the related data generated by digital activities, and this data tells a good story about habits and preferences. Data exhaust consists of virtual trails left behind, similar to the exhaust from a vehicle, a byproduct that reveals the trail it has taken. This data is used to target advertisements to specific demographics and for market research, which tells businesses the online preferences, behaviors and habits of potential customers, giving them insight into how to mold their business into something that the people will consume. This is called behavioral targeting.
¶ In more legitimate science, this can be used to improve digital and online processes based on the behaviors of users. We can look for shortcuts to minimize required actions and find areas to optimize, improve or change outright. Data exhaust is widely used in data mining and big data analytics. (†2611)
disintermediation (s.v. "disintermediation"): A process that provides a user or end consumer with direct access to a product, service or information that would otherwise require a mediator such as a wholesaler, lawyer or salesperson.
¶ Disintermediation cuts out the middleman. By using the Internet, companies and even manufacturers can deal directly with users or end consumers, which is a significant factor in decreasing the cost of servicing customers. The high market transparency often enables the buyers to pay less as they deal directly with the manufacturer, bypassing the wholesaler and the retailer. As another alternative, buyers can also buy directly from wholesalers. (†2622)
security audit (s.v. "information security audit"): An organizational review to ensure that the correct and most up-to-date processes and infrastructure are being applied. An audit also includes a series of tests that guarantee that information security meets all expectations and requirements within an organization. (†2737)
