On this day I learned about the DBSCAN which is density based spatial clustering of applications with noise. DBSCAN algorithm can create clusters based on the density of the data points. Here number of clusters are created based on the density of data points. this method can be useful in identifying outliers, as data points away from the dense clusters can be easily marked as outliers.
In my opinion, the clustering techniques can be very useful in identifying patterns in the data points, such as the prevalence of shooting fatalities based on location i.e. regions with a high number of shootings, weapons used, demographic analysis, the intended use of force, temporal data for analysis the fluctuation of shooting over a period of time etc.