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Improving OLTP Data Quality Using Data Warehouse Mechanisms
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Matthias Jarke,
Christoph Quix,
Guido Blees,
Dirk Lehmann,
Gunter Michalk, and
Stefan Striel
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Return to Industrial Session: Database Techniques/Experience
Research and products for the integration of heterogeneous legacy source databases in data warehousing have addressed numerous data quality problems in or between the sources. Such a solution is marketed by Team4 for the decision support of mobile sales representatives, using advanced view maintenance and replication management techniques in an environment based on relational data warehouse technology and Lotus Notes-based client systems. However, considering total information supply chain management, the capture of poor operational data, to be cleaned later in the data warehouse, appears sub-optimal. Based on the observation that decision support clients are often closely linked to operational data entry, we have addressed the problem of mapping the data warehouse data quality techniques back to data quality measures for improving OLTP data. The solution requires a warehouse-to-OLTP workflow which employs a combination of view maintenance and view update techniques.
Note: References link to DBLP on the Web.
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@inproceedings{DBLP:conf/sigmod/JarkeQBLMS99,
author = {Matthias Jarke and
Christoph Quix and
Guido Blees and
Dirk Lehmann and
Gunter Michalk and
Stefan Striel},
editor = {Alex Delis and
Christos Faloutsos and
Shahram Ghandeharizadeh},
title = {Improving OLTP Data Quality Using Data Warehouse Mechanisms},
booktitle = {SIGMOD 1999, Proceedings ACM SIGMOD International Conference
on Management of Data, June 1-3, 1999, Philadephia, Pennsylvania,
USA},
publisher = {ACM Press},
year = {1999},
isbn = {1-58113-084-8},
pages = {536-537},
crossref = {DBLP:conf/sigmod/99},
bibsource = {DBLP, http://dblp.uni-trier.de} } },
Copyright(C) 2000 ACM
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