3 Adding Semantics to Business Intelligence: Towards a Smarter Generation of Analytical Tools Denilson Sell 1,2,3 , Dhiogo Cardoso da Silva 2 , Fernando Benedet Ghisi 1,2 , Márcio Napoli 1,2 and José Leomar Todesco 1,2 1 Instituto Stela, 2 UFSC – Universidade Federal de Santa Catarina, 3 UDESC – Universidade do Estado de Santa Catarina, Brazil 1. Introduction Fierce competition in the digital economy and increasing volume of available data are forcing organizations to find efficient ways to gain valuable information and knowledge to improve the efficiency of their business processes. Business Intelligence (BI) solutions offer the means to transform data to information and derive knowledge through analytical tools in order to support decision making. Analytical tools should support decision makers to find information quickly and enable them to make well-informed decisions. Despite the importance of analytical tools to organizations, there are challenges that should be tackled in order to leverage the impact of those tools in the decision making process. These challenges include difficulties to extend those tools according to the business requirements, no support to analyze and interpret data and lack of flexibility to customize information presentation according to users’ profile. We argue that these issues are due to the lack of integration of business’ semantics into the foundations of analytical tools. Our approach applies ontologies on the description of business rules, information sources and business concepts in order to support semantic- analytical functionalities that extend traditional OLAP operations. Such approach enables developers to customize BI solutions according to organizations’ specific analytical requirements and allows developers to align BI solutions to the latest business analytic requirements. In addition, this approach made it possible to offer novel approaches to guide decision makers on the analysis of their business, including recommendation according to users’ profile, a question answering approach to access business data and automatic generation of text summaries based on OLAP cubes. The improvements on knowledge engineering and related technologies offer new approaches to tackle traditional issues in the context of information management. In this chapter, we describe how Semantic Web technologies and business semantics were applied on the conception of an architecture for analytical tools. Our ultimate goals are to contribute www.intechopen.com