Data Reduction Strategies Data reduction techniques can be applied 1o obtain a reduced representation of the data set that is much smaller in volume, yet. closely maintains the integrity of the original data, That is, mÃning on the reduced data set should be more efficient yet produce the same analytical results Data Cube Aggregation, where aggregation operations are applied to the data in the construction of a data cube. Attribute Subset Selection, where irrelevant, weakly relevant, or redundant attributes of dimensions may be detected and removed. Dimensionality Reduction, where the encoding mechanisms are used to reduce the data set size. Numerosity Reduction, where the data are replaced or estimated by alternative smaller data representations such as parametric models or no parametric methods such as clustering camping, and the use of histograms. Discretization and Concept Hierarchy Generation, where ranges or higher conceptual levels replace raw data values for attributes. Data d