Using approximations to scale exploratory data analysis in datacubes
Daniel Barbará, Xintao Wu · 1999
Exploratory Data Analysis is a widely used technique to determine which factors have the most influence on data values in a multi-way table, or which cells in the table can be considered anomalous with respect to the other cells. In particular, median polish is a simple, yet robust method to perform Exploratory Data Analysis. Median polish is resistant to holes in the table (cells that have no values), but it may require a lot of iterations through the data. This factor makes it difficult to apply median polish to large multidimensional tables, since the I/O requirements may be prohibitive. This paper describes a technique that uses median polish over an approximation of a datacube, easing the burden of I/O. The results obtained are tested for quality, using a variety of measures. The technique scales to large datacubes and proves to give a good approximation of the results that would have been obtained by median polish in the original data. 1 Introduction Exploratory Data...