A statistical technique to transform high-dimensional data into a lower-dimensional space while preserving as much information about the original data as possible.

• Data compression
• Image recognition
• Stock market predictions
• Quantitative finance
• Genomics
• Neuroimaging
• Meteorology

PCA is commonly used in image and text analysis to reduce the dimensionality of large datasets while retaining important features. For example, in image analysis, PCA can be used to reduce the number of pixels in an image while preserving the most important details.

• Data inventory and analysis