Data mining tools are now available to enhance decisionmaking and analysis in the State and local law enforcement arena. The newer data mining tools do not require huge IT budgets, specialized personnel, or advanced training in statistics. These products are highly intuitive, relatively easy to use, PC-based, and very accessible to the law enforcement community. Data mining encompasses the process of discovering hidden patterns and relationships in large amounts of information. This allows for making accurate and reliable predictions of future events, based on the identification and characterization of these patterns and trends in historical data. Data mining can be used in law enforcement to discover new patterns or confirm suspected patterns or trends. The primary use of data mining is to find something new in the data - to discover a new piece of information that no one knew previously. This is sometimes referred to as the bottom-up or data-driven approach because it starts with the data and then builds theories based on discovered patterns or trends. Confirmation starts with an idea about a possible relationship (a hypothesis) and seeks to verify or refute the hypothesis based on the data. The discovery and confirmation approaches are complementary and are often applied in alternating sequence. The most important required skill for data mining is domain knowledge, which means one is in the position to evaluate the value or validity of the results. Data mining tools are used by law enforcement organizations in a variety of analytical applications, including deployment, risk-based deployment, tactical crime analysis, behavioral analysis of violent crime, risk and threat assessment, officer safety, and around-the-clock crime analysis. The successful use of data mining and predictive analytics in law enforcement and intelligence analysis represents a powerful new tool, as well as a significant paradigm shift for the police executive. 6 endnotes