The use of location data has gained significant attention lately, with organizations leveraging it to enhance marketing efficiency, reduce risk, improve medical research, and facilitate urban planning. However, despite its potential benefits, many businesses are slow to adopt location data due to the complexity of integrating new digital infrastructure, such as the Internet of Things, machine learning, artificial intelligence, and predictive analytics. Location data can be applied in all four types of analytic methods: Descriptive, Diagnostic, Predictive, and Prescriptive. Descriptive analytics provides a summary of historical data, while diagnostic analytics examines data to understand causes of events and behaviors. Predictive analytics identifies likelihood of future outcomes based on historical data, and prescriptive analytics finds the best course of action for a given situation. Location intelligence is not just another information system, but a powerful set of capabilities that can augment other business intelligence solutions, allowing organizations to unlock the power of geospatial data and apply geographic contexts to business data.