Geoanalytics is a catchall term for the discipline of data science that deals with spatial parameters. This exists within the realm of GIS (Geographic Information Systems). Professional geographers have been working with this type of data for generations in various forms to provide insights and answers to the burning questions that keep industry and government leaders up at night. Geographic data provides unique insights in various decision-making spaces, but its usage might not seem obvious at first. The truth is that professionals rely upon analytics across disciplines to ensure smooth policy coordination and sound decision-making that creates future growth in all aspects of social policy development.
Government usage of these datasets has long been a key feature in the process of policy decision-making. Queries surrounding funding allocation, threat assessment, and disaster relief efforts combat real-time events all piggyback off of geographical data analysis and the location’s unique context. Open-source maps are a great start for any application of this analytical data. Still, many of these processes utilize the high-resolution imagery provided by a growing array of infrastructure in the upper atmosphere.
Geoanalytics helps government processes function through complex event processing (CEP). This analytical framework helps entities across the spectrum create analysis and frameworks for response generation automatically. Many of the threats faced by our local and national governing bodies are minor blips on the radar. They require a simple adjustment in real-time to account for the variance or trouble that would otherwise disrupt citizens’ daily lives in this or that part of the country. For these challenges, governments rely on a CEP framework – Complex Event Processing. This is an algorithmic approach to problem-solving that requires an input of big data analytics and geospatial datasets to create a systematic evaluation of the threat matrix faced at any given juncture in time or place. Because of the natural variations in population density, landscape, infrastructure, and local hazards and challenges, the GIS domain remains supreme in directing event stream processing functions.
Advertising is an industry that relies on crucial GIS data products for efficient market penetration. The correlation between demographic breakdowns and the physical space in which these markers can be found is crucial in the targeted ad buys that run the ad world. Frankly, an advertising agency’s ability to tap into this crossover between demography and geography is its greatest asset for running ads for clients. Firms that understand the value of insights derived from physical space are positioned ahead of the pack when it comes to targeting your intended audience.
Manufacturing tasks also require analytics insights as well. The industry is built on efficient supply chain management, which means a factory operator must always know exactly where raw materials are in the possession chain. Creating products for consumers demands a constant influx of supplies and a corresponding outflow of the finished products. For this, managers rely on sophisticated GIS data to track the movements of each component piece of the puzzle.
This way, the core team can assign tasks to floor personnel or schedule additional time off to coincide with a lull in deliveries or availability of essential parts. Maintaining high efficiency here is the difference between success and failure, and the physical location of each moving piece dictates the standard operating costs that a manufacturing hub must endure. Location is a crucial consideration when evaluating any task, from the factory floor through to satellite operation. Everywhere you look these days, geospatial data takes center stage, and for a good reason.