Enhancing Data Warehouse management through semi-automatic data integration and complex graph generation

Abstract

Strategic information is one of the main assets for many organizations and, in the next future, it will become increasingly more important to enable the decisionmakers answer questions about their business, such as how to increase their profitability. A proper decision-making process is benefited by information that is frequently scattered among several heterogeneous databases. Such databases may come from several organization systems and even from external sources. As a result, organization managers have to deal with the issue of integrating several databases from independent data sources containing semantic differences and no specific or canonical concept description. Data Warehouse Systems were born to integrate such kind of heterogeneous data in order to be successively extracted and analyzed according to the manager’s needs and business plans. Besides being difficult and onerous to design, integrate and build, Data Warehouse Systems present another issue related to the difficulty to represent multidimensional information typical of the result of OLAP operations, such as aggregations on data cubes, extraction of sub-cubes or rotations of the data axis, through easy to understand views... [edited by author]