Data Warehousing on Nonconventional Data
Non-conventional data are any kind of data that are useful for business intelligence (BI) but that cannot be directly managed with traditional data warehousing (DW) technology. Non-conventional data cover a great variety of user-generated contents such as domain knowledge, corporate documents like contracts and e-mails, news feeds, messages posted on social media, and so on. Non-conventional data sources have in common a semi-structured, dynamic, and text-rich nature, which make difficult their integration within traditional corporate information systems (including data warehouses). Nowadays, non-conventional data mainly reside in the Web, adopting the standard formats proposed by the World Wide Web Consortium (W3C), like HTML, XML, RSS, RDF, etc. This entry is focused on those approaches aimed to either integrate non-conventional data with traditional DW/OLAP or to perform ad hoc DW of these data sources. This entry does not account for approaches that adopt Web languages...
- 2.Bhide MA, Gupta A, Gupta R, Roy P, Mohania MK, Ichhaporia Z. LIPTUS: associating structured and unstructured information in a banking environment. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data; 2007. p. 915–24.Google Scholar
- 3.Castellanos M, Wang S, Dayal U, Gupta C. SIE-OBI: a streaming information extraction platform for operational business intelligence. In: Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data; 2010. p. 1105–10.Google Scholar
- 4.Chakaravarth, VT, Gupta H, Roy P, Mohania M. Efficiently linking text documents with relevant structured information. In: Proceedings of the 32nd International Conference on Very Large Data Bases; 2006. p. 667–78.Google Scholar
- 5.Francia M, Golfarelli M, Rizzi S. A methodology for social BI. In: Proceedings of the 18th International Database Engineering & Applications Symposium; 2014. p. 207–16.Google Scholar
- 10.Park B, Song I. Incorporating text OLAP in business intelligence. In: Zorrilla M, Mazón J, Ferrández Ó, Garrigós I, Daniel F, Trujillo J, editors. Business intelligence applications and the web: models, systems and technologies. Hershey: IGI Global; 2012.p. 77–101.Google Scholar