the benefits of the interaction between data warehouses and question answering
Business Intelligence (BI) applications allow their users to query, understand, and analyze existing data within their organizations in order to acquire useful knowledge, thus making better decisions. The core of BI applications is a data warehouse (DW) which integrates several heterogeneous data sources, mainly structured transactional databases. However, a new trend has emerged, since users of BI applications no longer limit their analysis to structured databases, and they also need unstructured sources to empower their analysis (i.e. data from the Web, company-internal reports, emails, etc.). Therefore, the ability to manage this available information is crucial for the success of the decision making process. Unfortunately, this new useful data, although easily available for companies, are often found in unstructured data (such as web pages, internal reports, emails, and so on) which make it unuseful for feeding the DW beneath BI applications. To shed light on this scenario, in this paper, we propose a novel model for using ontologies to integrate Question Answering (QA) systems in the DW. The great benefit of using QA is that specific pieces of data (i.e. answers) that will empower the analysis are detected, obtained and returned from unstructured data in order to feed the DW.
data warehouse question answering business intelligence ontology information retrieval