Data as a service yearly). The drawbacks of data as a service are generally similar to those associated with any type of cloud computing, such as the reliance of the customer on the service provider's ability to avoid server downtime. Specific to the DaaS model, a common criticism is that when compared to traditional data delivery, the consumer is really just "renting" the data, using it to produce a graph, chart or map, or possibly perform analysis, but for data as a service, generally the data is not available for download. "Service automation units" (code that expresses the service interface) may contain methods for
Data-intensive computing information exists in unstructured form with increased data processing requirements compared to structured information. The storing, managing, accessing, and processing of this vast amount of data represents a fundamental need and an immense challenge in order to satisfy needs to search, analyze, mine, and visualize this data as information. Data-intensive computing is intended to address this need. Parallel processing approaches can be generally classified as either "compute-intensive", or "data-intensive". Compute-intensive is used to describe application programs that are compute bound. Such applications devote most of their execution time to computational requirements as opposed to I/O, and typically require small volumes