Managing Time Consistency for Active Data Warehouse Environments
Real-world changes are generally discovered delayed by computer systems. The typical update patterns for traditional data warehouses on an overnight or even weekly basis enlarge this propagation delay until the information is available to knowledge workers. Typically, traditional data warehouses focus on summarized data (at some level) rather than detail data. For active data warehouse environments, also detailed data about individual entities are required for checking the data conditions and triggering actions. Hence, keeping data current and consistent in that context is not an easy task. In this paper we present an approach for modeling conceptual time consistency problems and introduce a data model that deals with timely delays. It supports knowledge workers, to find out, why (or why not) an active system responded to a certain state of the data. Therefore the model enables analytical processing of detail data (enhanced by valid time) based on a knowledge state at a specified instant of time. All states that were not yet knowable to the system at that point in time are consistently ignored.
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- 3.Bliujute, R., Saltenis, S., Slivinskas, G., Jensen, C.S.: Systematic Change Management in Dimensional Data Warehousing. Technical Report TR-23, TIMECENTER, January 1998.Google Scholar
- 4.Böhlen, M.H., Busatto, R., Jensen, C.S.: Point-Versus Interval-Based Temporal Data Models. Proc. of 14th Intl. Conf. ICDE, IEEE Comp. Society Press, pp. 192–201, Orlando, USA, 1998.Google Scholar
- 7.English, L.P.: Improving Data Warehouse and Business Information Quality. John Wiley and Sons, New York, 1999.Google Scholar
- 8.Inmon, W.H.: Building the Data Warehouse. John Wiley and Sons, New York, 1996.Google Scholar
- 9.Jensen, C.S., Dyreson, C.E., (eds): The Consensus Glossary of Temporal Database Concepts. In Temporal Databases: Research and Practice, Springer, LNCS 1399, pp. 367–405, 1998.Google Scholar
- 11.Roddick, J.F., Schrefl, M.: Towards an Accommodation of Delay in Temporal Active Databases. Proceedings of the 11th Australasien Database Conference (ADC2000), IEEE Computer Society, pp. 115–119, Canberra, Australia, 2000.Google Scholar
- 14.Schrefl, M., Thalhammer, T.: On Making Data Warehouses Active. Proceedings of the 2nd International Conference DaWaK, Springer, LNCS 1874, pp. 34–46, London, UK, 2000.Google Scholar
- 17.Westerman, P.: Data Warehousing: Using the Wal-Mart Model. Morgan Kaufmann Publishers, San Francisco, 2001.Google Scholar
- 18.Yang, J., Widom, J.: Temporal View Self-Maintenance. Proceedings of the 8th Intl. Conf. EDBT2000, Springer, LNCS 1777, pp. 395–412, Konstanz, Germany, 2000.Google Scholar
- 19.Zaniolo, C., Ceri, S., Faloutsos, C., Snodgrass, R.T., Subrahmanian, V.S., Zicari, R.: Advanced Database Systems. Morgan Kaufmann Publishers, San Francisco, 1997.Google Scholar