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The majority of enterprises are in the process of recognizing that business data analytics have the potential to transform their daily operations and make them extremely effective at addressing business challenges, identifying new market trends and embracing new ways to engage customers. Such analytics are in most cases related with the processing of data coming from various data sources that include structured and unstructured data. In order to get insight through the analysis results, appropriate input has to be provided that in many cases has to combine data from cross-sectorial and heterogeneous public or private data sources. Thus, there is inherent a need for applying novel techniques in order to harvest complex and heterogeneous datasets, turn them into insights and make decisions. In this paper, we present an approach for the production of added-value business analytics through the consumption of interlinked versions of data and the exploitation of linked data principles. Such interlinked data constitute valuable input for the initiation of an analytics extraction process and can lead to the realization of analysis that was not envisaged in the past. In addition to the production of analytics based on the consumption of linked data, the proposed approach supports the interlinking of the produced results with the associated input data, increasing in this way the value of the produced data and making them discoverable for further use in the future. The designed business analytics and data mining component is described in detail, along with an indicative application scenario combining data from the governmental, societal and health sectors.

Exploiting Linked Data Towards the Production of Added-Value Business Analytics and Vice-versa