A popular belief holds that the next revolution in the web will be the effort and presumed eventual success in organizing, analyzing, and interpreting all of the data that the previous revolution facilitated. While it is an obvious next step, the path towards it is profoundly difficult. In the fast-paced, marketing-oriented start-up world, a suite of end-user analytical processes for social media data have cropped up. While possibly earnest attempts, their lax attitude towards statistical rigor, lack of transparency, and over-simplification of very complex online phenomena leaves users worse off. At the same time, popular sites of interest, such as Facebook and Twitter, make it very difficult for researchers to analyze, share, and present data. In this presentation, one social media site of research interest, Twitter, is considered, and an alternate approach to analytics is exhibited as a possible workflow going forwards.