Integration of Structured and Unstructured Data in the Financial Analysis Domain - A State of the Art

摘要

There is a consensus (Hoffman and Strand, 2001; Hannon, 2002; Bovee et al., 2005; Willis, 2005; Cox, 2006) that XBRL (Extensible Business Reporting Language) as a technical standard for facilitating transfer and analysis of financial statements could improve the speed and quality of transmitting, analyzing, and even more accurate financial reports by providing machine readable documents. Footnotes, which include important explanations about financial values, have still an unstructured format and are an obstacle for analysts and other stakeholders who want to benefit from analyzing financial statements. It is of interest how data integration approaches can support and facilitate the process of data extraction from footnotes automatically to gain accurate and reasonable analysis to avoid manual tasks. To address this issue, a state of the art is needed to identify and cluster relevant existing methods in terms of structured and unstructured data integration. It is shown that most of the existing literature is focused on a storage level of data integration. Other researchers deal with methods and tools to integrate and analyze structured and unstructured data separately. But, no identified paper illustrates an unstructured data integration solution to support analytical tasks based on XBRL documents.