Data clustering techniques are used in various fields like engineering, medicine, and business to organize complex data. Different methods like density-based clustering and K-means clustering are used to group similar data points together. A recent book reviews these techniques and algorithms, discussing how they measure similarity between data points, assess clustering algorithms, and apply clustering methods in insurance, psychology, and other areas.