Over the last two decades, there has been an increasing trend to incorporate and enable spatial data, visualization, analysis in the context of the applications, development tools, services, UI, and analytics. Today, the focus is on including native spatial capabilities across platform technologies, applications, and cloud services. Applications and SaaS services use spatial visualization and analysis to provide context and information relevant to the applications; our technology stack — database, development tools, platform services — incorporates spatial analysis, understands spatial datatypes, and supports spatial services including 2D/3D vector data, point clouds, topology, raster and remote sensing, and networks, thus fully embracing the essential role geospatial plays in all modern applications and services.
Digital Technologies: Shaping the future
In a geospatial context, it is the time to embrace, extend, and innovate keeping up with the major trends in the technology field — autonomous services, self-service and low code interactions, Cloud-native capabilities, and implicit mobility. Today, everything is based and offered on new and emerging Cloud and autonomous architectures as well as embracing ML and AI technologies. But, so do players outside the traditional geospatial industry who have entered as disrupters or from a different perspective. This creates a dynamic where more established geospatial industry players can be followers because while we understand the opportunity, we may not be as focused or agile as non-traditional entrants.
The industry plays a crucial role in this changing approach from a number of perspectives. First, the Internet of Things and predictive data from artificial intelligence and machine learning allows us to provide more relevant and contextually appropriate spatial analysis or location-enabled information. Second, the “signal” that is generated from spatial analysis can feed ML and analytics to provide more relevant results. Taking all this into consideration, Oracle develops applications, technology and services that use AI, ML and IoT technologies with geospatial from both of these dimensions.
What the geospatial industry can do differently is to offer more data, more “service-based” offerings, and more VR/AR and hybrid reality offerings. Companies like ours should continue to invest significantly in R&D and new product development and focus on geospatially-enabled self-service/autonomous services and real-time sensor-based advanced analytic capabilities based on Internet of Things (IoT) and machine learning technologies.
The future lies in integrating technologies. Geospatial silos are increasingly unacceptable in modern technology architectures. Oracle presents data through industry-standard APIs (not only geospatial standards) and formats. We also enable access to analysis and results sets in application context; our approach is not to depend on users and applications to learn the geospatial concept but to deliver geospatial information and analysis as consumable services in the context of the user or application.