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EN
Microgeneration of energy has the potential to become an important component of the energy policy of many governments, because it may substantially lower carbon emissions and reduce the need for new infrastructure. Nevertheless, from recent studies it follows that, even in the developed countries, microgeneration technology is far from being widely adopted. In this study, we use data collected in a survey conducted in Lower Silesia, a south-western region of Poland, to build behavioural profiles of energy consumers, in order to get some insights into barriers to microgeneration becoming extensively adopted. In particular, we exploit the decision tree method to determine typical attributes of potential prosumers, to find the relative importance of these attributes and, finally, to make some predictions based on data that were not used in constructing the model. From our findings, it follows that economical criteria are the most important triggers for considering the installation of microgeneration technologies. Thus any governmental initiative promoting pro-ecological behaviours, including the use of renewable energy sources, should be based primarily on financial incentives to succeed.
EN
One of the main issues of operators today is to be able not only to store and manage the huge amount of data generated by the applications and customer contact points, but also to give value to these data. But this implies using tools for storing the data, to manage it, look at it, understand it, exploit it, generate actions such as marketing campaigns. It is therefore obvious that using one tool for each of these functions will discuss here the technical issues involved and show how we turned them into an easy-to-use solution for business users.
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