The Database Group at MIT’s Computer Science and Artificial Intelligence Laboratory has released a data-visualization tool that lets users highlight aberrations and possible patterns in the graphical display; the tool then automatically determines which data sources are responsible for which. It could be, for instance, that just a couple of faulty sensors among dozens are corrupting a very regular pattern of readings, or that a few underperforming agents are dragging down a company’s sales figures, or that a clogged vent in a hospital is dramatically increasing a few patients’ risk of infection. For his thesis work, Eugene Wu, a graduate student in electrical engineering and computer science who developed DBWipes with Madden and adjunct professor Michael Stonebraker, designed a novel “provenance tracking” system for large data sets. Continue reading this article on MIT News.
Wu creates data-visualization tool
September 18, 2014