An alternative data warehouse reference architectural configuration

Victor González-Castro, Lachlan M. MacKinnon, María Del Pilar Angeles

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In the last few years the amount of data stored on computer systems is growing at an accelerated rate. These data are frequently managed within data warehouses. However, the current data warehouse architectures based on n-ary-Relational DBMSs are overcoming their limits in order to efficiently manage such large amounts of data. Some DBMS are able to load huge amounts of data nevertheless; the response times become unacceptable for business users during information retrieval. In this paper we describe an alternative data warehouse reference architectural configuration (ADW) which addresses many issues that organisations are facing. The ADW approach considers a Binary-Relational DBMS as an underlying data repository. Therefore, a number of improvements have been achieved, such as data density increment, reduction of data sparsity, query response times dramatically decreased, and significant workload reduction with data loading, backup and restore tasks. © 2009 Springer Berlin Heidelberg.

Original languageEnglish
Title of host publicationDataspace: The Final Frontier - 26th British National Conference on Databases, BNCOD 26, Proceedings
Pages33-41
Number of pages9
Volume5588 LNCS
DOIs
Publication statusPublished - 2009
Event26th British National Conference on Databases - Birmingham, United Kingdom
Duration: 7 Jul 20099 Jul 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5588 LNCS
ISSN (Print)0302-9743

Conference

Conference26th British National Conference on Databases
Abbreviated titleBNCOD 2009
Country/TerritoryUnited Kingdom
CityBirmingham
Period7/07/099/07/09

Keywords

  • Alternative Data Model
  • Architectural Configuration
  • Binary-Relational
  • Column DBMS
  • Data Warehouse
  • Database Explosion

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