1. A method for determining a driving factor for a data value of interest in a multidimensional database, the method comprising: collecting a context for the data value of interest in the multidimensional database, wherein the data value of interest having a first plurality of dimensions and a drill path, wherein the context comprises an intersection of the first plurality of dimensions, wherein the drill path comprises a first plurality of dimensional levels connected to the first plurality of dimensions, wherein a second plurality of dimensions not directly connected to the first plurality of dimensions comprises dimensions outside the context and outside the drill path, wherein a second plurality of dimensional levels comprise dimensional levels connected to the second plurality of dimensions, the first and the second pluralities of dimensional levels each having dimensional members; applying the context of the data value of interest to each of the second plurality of dimensional levels to generate a query for each of the second plurality of dimensional levels, wherein, for each of the second plurality of dimensional levels, the query for that dimensional level, when executed, queries the intersection of 1) the first plurality of dimensions, and 2) each of the dimensional members of that dimensional level; executing, by one or more computing devices, the query for each of the second plurality of dimensional levels using the dimensional members of each of the second plurality of dimensional levels to generate a set of data values for each of the second plurality of dimensional levels, wherein each data value of the set of data values is calculated by at least applying a value of one of the dimensional members of one dimensional level of the second plurality of dimensional levels to the data value of interest, wherein a subset of the second plurality of dimensional levels outside the context and the drill path is used for executing the query; calculating a variance of the set of data values generated for each dimensional level of the second plurality of dimensional levels; identifying one of the dimensional levels of the second plurality of dimensional levels as having a greatest variance of the calculated variances; selecting the identified dimensional level as the driving factor; generating a new data value of interest having a new context that comprises an intersection of the first plurality of dimensions and a dimension of the driving factor; selecting the new data value of interest; removing levels involved with the new data value of interest from the second plurality of dimensional levels; determining a new driving factor; and adding the new driving factor to the context.