Data reduction techniques

Data reduction techniques are methods used to simplify complex data sets by removing unnecessary or redundant information, making data easier to analyze and interpret. Examples include selecting the most relevant features (feature selection), summarizing data with statistics (like averages), or combining data points (aggregation). These techniques help improve processing speed, reduce storage needs, and highlight key insights without losing essential information. Essentially, data reduction makes large, complicated data more manageable and meaningful for making decisions or generating reports.