Improving OLTP data quality using data warehouse mechanisms

Authors:
Matthias Jarke;Christoph Quix;Guido Blees;Dirk Lehmann;Gunter Michalk;Stefan Stierl
Affiliations:
Informatik V, RWTH Aachen, D-52056 Aachen, Germany;Informatik V, RWTH Aachen, D-52056 Aachen, Germany;Team4 Systemhaus GmbH, D-52134 Herzogenrath, Germany;Team4 Systemhaus GmbH, D-52134 Herzogenrath, Germany;Team4 Systemhaus GmbH, D-52134 Herzogenrath, Germany;Team4 Systemhaus GmbH, D-52134 Herzogenrath, Germany
Venue:
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Year:
1999

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Abstract

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.