Data Cube

A Data Cube is a multi-diomensional array data structure that is arranged in rows and columns in order to be visualized as a three-dimensional array (i.e a cube).

References

(Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/Data_cube Retrieved:2017-6-11.
- In computer programming contexts, a data cube (or datacube) is a multi-dimensional array of values, commonly used to describe a time series of image data.
  The data cube is used to represent data along some measure of interest. Even though it is called a 'cube', it can be 1-dimensional, 2-dimensional, 3-dimensional, or higher-dimensional.
  Every dimension represents a new attribute in the database and the cells in the cube represent the measure of interest.

(Zaiane, 1999a) ⇒ Osmar Zaiane. (1999). “Glossary of Data Mining Terms." University of Alberta, Computing Science CMPUT-690: Principles of Knowledge Discovery in Databases.
- QUOTE: Data Cube: Also Cube, Hypercube, Multi-dimentional Array, Multi-dimentional Database. It is a multi-dimentional data structure, a group of data cells arranged by the dimensions of the data. For example, a spreadsheet exemplifies a two-dimensional array with the data cells arranged in rows and columns, each being a dimension. A three-dimensional array can be visualized as a cube with each dimension forming a side of the cube, including any slice parallel with that side. Higher dimensional arrays have no physical metaphor, but they organize the data in the way users think of their enterprise. Typical enterprise dimensions are time, measures, products, geographical location, sales channels, etc. It is not rare to see more than 20 dimensions. However, the higher the dimensions the more complex the manipulation and data mining on the cube become, and the more sparce the data cube may become.

(Agarwal et al., 1996) ⇒ Agarwal, S., Agrawal, R., Deshpande, P. M., Gupta, A., Naughton, J. F., Ramakrishnan, R., & Sarawagi, S. (1996, September). On the computation of multidimensional aggregates. In VLDB (Vol. 96, pp. 506-521).
- Tools for multidimensional data analysis comprise a large and fast-growing industry (estimates vary widely, but go as high as $700M for 1995[3]). Recently there has been a lot of research interest in this area. One of the earlier papers is by Gray et al. [1], where multidimensional aggregation is formalized and expressed in SQL by new operator called the CUBE operator. The CUBE operator is the multidimensional generalization of the group-by operator. The CUBE operator on n dimensions is equivalent to a collection of group-by statements, one for each subset of the n dimensions (...)

(NCSA,1995) ⇒ http://archive.ncsa.illinois.edu/Cyberia/Bima/DaCub.html
- Data Cube Representation: Sometimes it is easiest for astronomers to understand the shape of an object, and the motion of the material that constitutes it by visualizing a data set in three dimensions. The data set, called a data cube, is rotated to make more apparent all three dimensions of the cube.
  A data cube is simply a three dimensional stacking of all the channel maps. Rather than seeing them sequentially as in the channel map movie, they are all visible at once through visualizing the cube as in the above movie. Being a compilation of channel maps, a data cube shows gas moving at all velocities, throughout the entire object. Two of a datacube's axes represent the spatial dimensions, while its third axis represents velocity.