Web farming and data warehousing for energy tradefloors

Abstract

The recent liberalisation of the German energy market forced the energy industry to develop and install new information systems to support agents on the energy trading floors in their analytical tasks. Besides classical approaches of building a data warehouse to give insight into the time series to understand market and pricing mechanisms it is crucial to provide a variety of external data from the Web. Weather information as well as political news or market rumors are relevant to give the right interpretation to the variables of a volatile energy market. Starting from a multidimensional data model and a collection of buy and sell transactions, a data warehouse is built that gives analytical support to the agents. Following the idea of Web farming, we harvest the Web, match the external information sources after a filtering and evaluation process to the data warehouse objects and present this qualified information on a user interface where market values are correlated with those external sources over the time axis.