In computing, data as a service, or DaaS, is a term used to describe cloud-based software tools used for working with data, such as managing data in a data warehouse or analyzing data with business intelligence. It is enabled by software as a service (SaaS). Like all "as a service" (aaS) technology, DaaS builds on the concept that its data product can be provided to the user on demand, regardless of geographic or organizational separation between provider and consumer. Service-oriented architecture (SOA) and the widespread use of APIs have rendered the platform on which the data resides as irrelevant. Data as a service as a business model is a concept when two or more organizations buy, sell, or trade machine-readable data in exchange for something of value. Overview DaaS began primarily in Web mashups and, since 2015, has been increasingly employed both commercially, and within organizations such as the United Nations. Traditionally, most organisations have used data stored in a self-contained repository, for which software was specifically developed to access and present the data in a human-readable form. One result of this paradigm is the bundling of both the data and the software needed to interpret it into a single package, sold as a consumer product. As the number of bundled software with data packages proliferated, and required interaction among one another, another layer of interface was required. These interfaces, collectively known as enterprise application integration (EAI), often tended to encourage vendor lock-in, as it is generally easy to integrate applications that are built upon the same foundation technology. The result of the combined software/data consumer package and required EAI middleware has been an increased amount of software for organizations to manage and maintain, simply for the use of particular data. In addition to routine maintenance costs, a cascading amount of software updates are required as the format of the data changes. The existence of this situation contributes to the attractiveness of DaaS to data consumers, because it allows for the separation of data cost and of data usage from the cost of a specific software environment or platform. Sensing as a Service (S2aaS) is a business model that integrates Internet of Things data to create data trading marketplaces. Vendors, such as MuleSoft, Oracle Cloud and Microsoft Azure, undertake development of DaaS that more rapidly computes large volumes of data; integrates and analyzes that data; and publish it in real-time,