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dc.contributor.author | Conradie, Pieter J.![]() |
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dc.contributor.author | Kruger, P.S. (Paul Stephanus), 1944-![]() |
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dc.date.accessioned | 2008-08-27T05:52:20Z | |
dc.date.available | 2008-08-27T05:52:20Z | |
dc.date.issued | 2006-05 | |
dc.description.abstract | Data quality, or rather the lack thereof, has been the downfall of many Data warehousing (DW) / Business Intelligence (BI) projects. The concept of Information Quality (IQ) has become increasingly important as the popularity of Business Intelligence (BI) increases. Industrial engineers have played a key role in the development and implementation of Total Quality Management (TQM) principles that are widely used in the manufacturing environment. In the information era, industrial engineers can apply the same principles to data. This article aims to identify strategies and processes to improve IQ that will eventually lead to data warehouses with complete, accurate and timely data that consistently meets the requirements of knowledge workers in their quest to make improved business decisions. | en |
dc.description.abstract | AFRIKAANS: Die gebrek aan datakwaliteit het al menige Databergings- en Besigheidsintelligensieprojekte laat sneuwel. Die konsep van Inligtingskwaliteit word al meer prominent soos die gewildheid van Besigheidsintelligensie toeneem. Bedryfsingenieurs het reeds ‘n sleutelrol gespeel in die ontwikkeling en implementering van Totale Kwaliteitsbestuurbeginsels wat algemeen in die vervaardigingsomgewing gebruik word. In die inligtingsera kan bedryfsingenieurs dieselfde beginsels ook op data toepas. Hierdie artikel identifiseer strategieë en prosesse om inligtingskwaliteit te verbeter wat uiteindelik behoort te lei tot datastore met volledige en akkurate data wat betyds en konsekwent aan kenniswerkers se behoeftes voldoen en hulle instaat stel om beter besigheidsbesluite te neem. | af |
dc.format.extent | 157460 bytes | |
dc.format.mimetype | application/pdf | |
dc.identifier.citation | Conradie, PJ & Kruger, PS 2006, 'The necessity of information quality for effective business intelligence', South African Journal of Industrial Engineering, vol. 17, no. 1, pp.129-147. [http://www.journals.co.za/ej/ejour_indeng.html] | en |
dc.identifier.issn | 1012-277X | |
dc.identifier.uri | http://hdl.handle.net/2263/6754 | |
dc.language.iso | en | en |
dc.publisher | Southern African Institute for Industrial Engineering | en |
dc.rights | Southern African Institute for Industrial Engineering | en |
dc.subject | Data warehousing (DW) | en |
dc.subject | Business intelligence (BI) | en |
dc.subject | Information quality (IQ) | en |
dc.subject | Knowledge workers | en |
dc.subject | Data quality | en |
dc.subject.lcsh | Data recovery (Computer science) | |
dc.subject.lcsh | Information retrieval -- Standards | |
dc.subject.lcsh | Total quality management | |
dc.subject.lcsh | Business intelligence | |
dc.title | The necessity of information quality for effective business intelligence | en |
dc.type | Article | en |