Big Data Addressed in Natural Language

Actions related to the cloud processing of large volumes of semi- or unstructured, streaming data (so-called “Big Data”) pose challenges that organizations must address. They are related to the location of the data in the cloud, its storage and management. Much of Big Data is collected from sources that are external to the business organization, such as social media, demographics, web data, events, news sources, and more. In this article, we discuss an access method to enable support for very large Big Data databases. It is based on the capabilities of Natural Language Addressing (NLA). An important advantage of NLA is the reduction of the amount of occupied memory due to the complete absence of additional indexes, absolute addresses, pointers and additional files, as well as the reduction of processing time due to the complete absence of searches - data is stored / retrieved to / from a direct address.