An important principle in managing any business is ‘What can't be measured, can't be managed’. The complexity of businesses today means that in order to measure business performance one needs to perform considerable analysis of data gathered in vast quantities on a regular basis. Therefore data analysis is at the heart of decision making in all business applications. There is, however, a significant degree of manual intervention in preparing, presenting and analysing business data. Recent advances in intelligent software technology have produced a number of novel techniques to model the human decision-making process. Data analysis tools have in the past been used by businesses mainly as a reactive tool. The pace of change and increased competition means that those businesses that can turn data into information and then into action quickly will have a better chance to survive and out-manoeuvre their rivals. This requires a fundamental change in the way data is used in the enterprise, from a reactive manner to a proactive one. The implications of recent changes can be significant on the level of skilled resources required as well as the cost of such operations. Intelligent software can play an important role in automating the analysis process and up-skill the business users. In this paper we will describe the intelligent business analytics (IBA) platform and two applications developed using it. The paper will focus on soft computing as an emerging technology suitable for incorporation into business analytics applications to model hidden patterns in data and to explain such patterns automatically.