multidimensional analysis
{{Short description|Data analysis process}}
In statistics, econometrics and related fields, multidimensional analysis (MDA) is a data analysis process that groups data into two categories: data dimensions and measurements. For example, a data set consisting of the number of wins for a single football team at each of several years is a single-dimensional (in this case, longitudinal) data set. A data set consisting of the number of wins for several football teams in a single year is also a single-dimensional (in this case, cross-sectional) data set. A data set consisting of the number of wins for several football teams over several years is a two-dimensional data set.
Higher dimensions
In many disciplines, two-dimensional data sets are also called panel data.{{cite book |first=G.S. |last=Maddala |title=Introduction to Econometrics |publisher=Wiley |year=2001 |isbn=0471497282 |edition=3rd}} While, strictly speaking, two- and higher-dimensional data sets are "multi-dimensional", the term "multidimensional" tends to be applied only to data sets with three or more dimensions.{{cite journal |last=Davies |first=A. |first2=K. |last2=Lahiri |title=A new framework for testing rationality and measuring aggregate shocks using panel data |journal=Journal of Econometrics |volume=68 |issue=1 |pages=205–227 |year=1995 |doi=10.1016/0304-4076(94)01649-K }} For example, some forecast data sets provide forecasts for multiple target periods, conducted by multiple forecasters, and made at multiple horizons. The three dimensions provide more information than can be gleaned from two-dimensional panel data sets.
Software
Computer software for MDA include Online analytical processing (OLAP) for data in relational databases, pivot tables for data in spreadsheets, and Array DBMSs for general multi-dimensional data (such as raster data) in science, engineering, and business.