tekom-Jahrestagung 2012 - ActiveDoc

Sprachtechnologie / Language Technology
Data Cubes
A valuable way to conceptualize the gathering of data for BI is the data
cube model. A data cube, also known as an OLAP (Online Analytical
Processing) cube, is an extension into three or more dimensions of the
type of two-dimensional, row and column data captured in spreadsheets,
whereby the third dimension represents an additional variable.
For example, a spreadsheet might capture products sold in rows, and the
locales in which they were sold in columns. Extending this data into a
third dimension would be like stacking the spreadsheet for this year on
top of that from last year, and these two on top of the spreadsheet from
the year before last, and so on.
Applied to the context of the language industry, one may envision a
cube made up of many individual cubes, each of which represents the
intersection of the three dimensions. For simplicity’s sake, the cube in
following example is 3x3x3, but this does not have to be the case. The
top horizontal layers in the cube represent the languages into which
translations were done. The vertical front-to-back layers represent new
words, fuzzy matched words, and repeated words in each language, and
the vertical left-to-right layers represent the years in which translations
were done. Each small cube represents a number at the intersection of
the three dimensions, for example, how many new words were translated
into Arabic in 2011.
Although it is certainly possible to drill down to them, the individual
intersection cubes are not necessarily interesting in and of themselves.
They provide greater insight for management decisions when they are
compared in sequence to other like cubes. In this example, the drilldown
looks at the intersection of fuzzy matched words in Arabic across
all three years, as indicated by the red cubes.
By rotating the cube and eliminating the extraneous data, we are left
with the sequence of numbers across all three years.
tekom-Jahrestagung 2012
253