What is data reduction in research

Data reduction is a method of reducing the volume of data thereby maintaining the integrity of the data. There are three basic methods of data reduction dimensionality reduction, numerosity reduction and data compression.

1. What do you mean by data reduction?
2. What are data reduction techniques in research?
3. What is an example of data reduction?
4. What is the purpose of data reduction?

What do you mean by data reduction?

Data reduction means the reduction on certain aspects of data, typically the volume of data. The reduction can also be on other aspects such as the dimensionality of data when the data is multidimensional. Reduction on any aspect of data usually implies reduction on the volume of data.

What are data reduction techniques in research?

There are at least four types of Non-Parametric data reduction techniques, Histogram, Clustering, Sampling, Data Cube Aggregation, Data Compression.

What is an example of data reduction?

Sampling: One of the methods used for data reduction is sampling, as it can reduce the large data set into a much smaller data sample.

What is the purpose of data reduction?

The purpose of data reduction can be two-fold: reduce the number of data records by eliminating invalid data; or • produce summary data and statistics at different aggregation levels for various applications.