The main difference between a neural network and the usual data structure is that networks receive many streams of information, and output one result. When it is possible to give a quantitative analysis of the data, there is a method of adding it to the factors considered in forecasting. Networks are often used to make forecasts in the foreign exchange market, because you can configure them to interpret the data and then draw conclusions.