Introduction

Business Intelligence is the future of efficient management and improves profitability in today’s industry. Semantic web technologies provide much flexible knowledge gathering and processing platform on data. Data can be gathered and processed using various available technologies to find relationships base on reason. This knowledge can be stored and processed using RDF/OWL technologies and can quire by languages like SPARQL with available technology frameworks. Processing large amounts of unstructured data can be quite computation intensive process. This challenge can be overcome by parallelism and using techniques like Google Map Reduce.
Further by including Natural Language Processing the information analysis can be greatly eased out for the end user of the system. This will help the end users to make quick decisions which can lead to profitability in an organization.
The semantic web (SW) has been conceived as a means to build semantic spaces over web published contents so that web information can be effectively retrieved and processed by both humans and machines in a great variety of tasks
SW Formats: RDF(S) and OWL
In RDF there are three kinds of elements resources, literals, and properties. Resources are web objects (entities) that are identified through a URI, literals are atomic values such as strings, dates, numbers, etc.,
The ontology web language (OWL) mainly differs from RDFS in the underlying semantic formalism, which is founded in description logics (DL) . Indeed, OWL languages provide RDF/XML serializations of different DL languages.