Prototype for Macroeconomic Decision Support System with Spatial Databases Support

Network organized structures can be stored and subsequently represented using spatial databases. They are used in areas where the aspects connected to maps and photos are very important: weather, management of natural calamities (earthquakes, fires, cyclones, volcanoes, floods), transportation and macroeconomic fluctuations. Studying side by side several such networks may reveal new aspects that will support making Big Decisions. For such solutions, the latest computer technologies are required, such as storing and processing huge volumes of data, Cloud storing, retrieving data from multiple sources and even using alert messages from social networks. Also, spatial databases are optimized to store and allow optimal access to data regarding various spatial localized objects. In this paper we propose a decision support system’s prototype that uses macroeconomic indicators that are correlated with natural phenomena like cataclysm (flows, earthquakes, etc.) at regional level and using spatial representation. The data will be collected as social media from Google Trends with possible extension from social networks, forums, news, etc. We will show how Big Data leads to Big Decisions when processed in a decision support system.