During the past ten years, researchers in information systems (IS) have paid increasing attention to improving the quality of their research methodologies. They have studied reference disciplines to adopt as well as adapt theories and models to support their research, focused more carefully on developing instruments with acceptable psychometric qualities, and expanded their repertoire of tools for examining empirical data. There have been two encouraging developments in this respect. First, leading journals in IS have published papers which have discussed construct and instrument development, and the relative merits of different research methods, especially qualitative ones which have not been well understood or used by a substantial portion of the IS research community. Second, tile editors and reviewers of leading research journals have demanded that empirical work exhibit a good theoretical foundation and a high quality instrument development process. Along the same lines, the objective of this mini-track on research methods is to impart IS researchers with the knowledge to improve the quality of empirical research. The emphasis is on a topic which has not been discussed in detail in the literature, namely, the tools and the methods researchers can utilize to make sense out of empirical observations. The two panels in this track will focus on the two extremes of the empirical continuum - qualitative data and quantitative data. Within each of these two broad categories, the panelists will explain the different methods to examine data and point out the strengths and weaknesses of each. It is hoped that the audience will acquire an appreciation of the subtleties involved in collecting and analyzing data, be in qualitative or quantitative, as well as a respect for the difficulties faced by researchers when conducting empirical research of any kind.