Introducing Location Intelligence

Location data is data with a geographic dimension. Location data is everywhere as all actions that occur in or near the Earth's surface happen to use geographic aspects. It is generally referred to as any data with coordinates (latitude, longitude, and sometimes altitude) but also encompasses different aggregated geographic units, including addresses, zip codes, landmarks, districts, cities, regions, and much more.

Location intelligence, on the other hand, is the process of turning geographic (spatial) data into insights and business outcomes. Any data with a geographical position, either implicitly or explicitly, requires location-aware preprocessing methods, visualization, as well as analytical methods to derive insights from it. Thus, location intelligence applications can reveal hidden patterns of spatial relationships that cannot be derived through other normal means. It leads to better decision making on spatial problems, where things happen, why they happen in some places, and the spatial trends in time-series analysis. Understanding the location dimension of today's challenges in, industrial, retail, agricultural, climate, and environment, can lead to a better understanding of why economic, social, and environmental activities tend to locate where they are.

In this chapter, we give an overview of location data and location data intelligence. Here, we briefly introduce different location data types and location data intelligence applications and examples. We cover how to identify location data from publicly available open datasets. We briefly discuss and highlight the difference between location data and other non-geographic data. At the end of this chapter, we explore how location data fits into data science and what opportunities and challenges bring location data into the interdisciplinarity of data science. 

We will specifically focus on the following topics:

• Location data
• Location data intelligence
• Location data and data science
• A primer on Google Colab and Jupyter Notebooks