Data clustering is a technique used in data analysis to group similar items together based on their characteristics. By organizing data into clusters, analysts can identify patterns and relationships within large datasets, making it easier to understand and interpret the information. This method is widely used in various fields, including machine learning, marketing, and image processing. Clustering algorithms, such as K-means and hierarchical clustering, help automate the grouping process. These algorithms evaluate the similarities between data points and assign them to clusters accordingly. The result is a more structured dataset that can reveal insights and support decision-making in diverse applications.