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Abstract improving oltp data quality using data warehouse mechanisms.
| Content Provider | CiteSeerX |
|---|---|
| Author | Jarke, Matthias Michalk, Gunter Quix, Christoph Blees, Guido Lehmann, Dirk Stierl, Stefan |
| 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. 1 |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Operational Data Entry View Update Technique Relational Data Warehouse Technology Data Warehouse Replication Management Technique Numerous Data Quality Problem Total Information Supply Chain Management Heterogeneous Legacy Source Database Mobile Sale Representative Poor Operational Data Lotus Notes-based Client System Decision Support Client Oltp Data Warehouse-to-oltp Workflow Advanced View Maintenance View Maintenance Decision Support Data Warehouse Data Quality Technique Data Quality Measure |
| Content Type | Text |
