From conventional to multiversion data warehouse: Practical issues
2009 (English)In: Evolving Application Domains of Data Warehousing and Mining: Trends and Solutions, IGI Global, 2009, 41-63 p.Chapter in book (Refereed)
The Data warehouse is not an autonomous data store, because it depends upon its operational source(s) for data population. Due to changes in real-world scenarios, operational sources may evolve, but the conventional data warehouse is not developed to handle the modifications in evolved operational sources. Therefore, instance and schema changes in operational sources cannot be adapted in the conventional data warehouse without loss of information. Multiversion data warehouses are proposed as an alternative to handle these problems of evolution. In this chapter we discuss and illustrate how versioning is implemented and how it can be used in practical data warehouse lifecycle. It is designed as a tutorial for users to collect and understand the concepts behind a versioning solution. Therefore, the purpose of this chapter is to collect and integrate the concepts, issues and solutions of multiversion data warehouses in a tutorial-like approach, to provide a unified source for users that need to understand version functionality and mechanisms.
Place, publisher, year, edition, pages
IGI Global, 2009. 41-63 p.
Computer and Information Science
IdentifiersURN: urn:nbn:se:kth:diva-163018DOI: 10.4018/978-1-60566-816-1.ch003ScopusID: 2-s2.0-84899250232ISBN: 9781605668161OAI: oai:DiVA.org:kth-163018DiVA: diva2:804956
QC 201504142015-04-142015-03-262015-04-14Bibliographically approved