Using Object Deputy Model to Prepare Data for Data Warehousing

Zhiyong Peng, Qing Li, L. Feng, Xuhui Li, Junqiang Liu

Research output: Contribution to journalArticleAcademicpeer-review

12 Citations (Scopus)

Abstract

Providing integrated access to multiple, distributed, heterogeneous databases and other information sources has become one of the leading issues in database research and the industry. One of the most effective approaches is to extract and integrate information of interest from each source in advance and store them in a centralized repository (known as a data warehouse). When a query is posed, it is evaluated directly at the warehouse without accessing the original information sources. One of the techniques that this approach uses to improve the efficiency of query processing is materialized view(s). Essentially, materialized views are used for data warehouses, and various methods for relational databases have been developed. In this paper, we will first discuss an object deputy approach to realize materialized object views for data warehouses which can also incorporate object-oriented databases. A framework has been developed using Smalltalk to prepare data for data warehousing, in which an object deputy model and database connecting tools have been implemented. The object deputy model can provide an easy-to-use way to resolve inconsistency and conflicts while preparing data for data warehousing, as evidenced by our empirical study.
Original languageUndefined
Article number10.1109/TKDE.2005.154
Pages (from-to)1274-1288
Number of pages15
JournalIEEE transactions on knowledge and data engineering
Volume17
Issue number9
DOIs
Publication statusPublished - Sep 2005

Keywords

  • METIS-229582
  • DB-DW: DATA WAREHOUSING
  • EWI-6319
  • data warehousing
  • data fusion/integration
  • object deputy model
  • duplicate handling
  • conflict resolution
  • Data preparation
  • IR-63246

Cite this

Peng, Z., Li, Q., Feng, L., Li, X., & Liu, J. (2005). Using Object Deputy Model to Prepare Data for Data Warehousing. IEEE transactions on knowledge and data engineering, 17(9), 1274-1288. [10.1109/TKDE.2005.154]. https://doi.org/10.1109/TKDE.2005.154