Since its introduction half a century ago IT has become one of the most important infrastructure components of virtually any organisation. An important key area of qualitative research in information systems is interviewing decision makers. These interviews aim to disclose hidden structures within IT projects and usage to increase their efficiency and effectiveness. In this context, the definition and analysis of critical success factors for information technology projects are well established areas for qualitative research in information systems. The analysis of critical success factors is of special importance since the IT projects still suffer from high failures rates. Therefore it is an important research goal within information systems to better understand IT projects to improve their success rates. The interviews of critical success factors provide a good data basis to disclose hidden structures in this domain. Besides only quantitatively interpreting such interviews the analysis can be enriched by some qualitative methods to support quantitative analysis and may disclose formerly hidden structures within the data. Therefore the objective of the paper is to enrich the analysis of IT projects and evaluate rough sets based quantitative analysis techniques for symbolic data which are characteristic in the domain of critical success factors analysis.