Traditional business intelligence provides answers about who, what and how, but struggles when the answer requires an understanding of the where. As operational business intelligence pushes the boundaries towards real-time, an understanding of location data is increasingly important for many businesses.

Next generation communications services, sensor networks, intelligent transportation, and fraud detection, all require location context to generate meaningful business intelligence, and all have a requirement for an understanding of the now.

Solutions today seek to integrate spatial data, sensor data and enterprise data in the data warehouse. Aside from the inherent delays in traditional data warehousing architectures, and the issues integrating spatial databases with enterprise data database, the major hurdle is the sheer volume of data. Sensors and intelligent handsets in particular generate a continuous flow of information, a large percentage of which is uninteresting.

Traditional solutions are therefore expensive, offer inadequate performance, poor scalability and ultimately fail to deliver real business value.

SQLstream enables you to combine your real-time data (sensors, intelligent devices, web portals) in real-time, providing instant updates against trends, and identifying patterns of behaviour or data associations as they occur. For example, roadside sensor data can be used to determine speed and traffic patterns in real-time; in-vehicle sensor data can be used to optimize logistics operations across all vehicles; real-time device data, clickstream data and service platform data can be combined to provide an accurate insight into the customers’ experience of your services.