Abstract
Traditional data warehouses are built in an off-line periodic fashion which makes them less valuable in applications where the most up-to-date data is required. For these applications, data should be incorporated in the warehouse and made available as soon as possible in “Real Time Data Warehouse”. In this paper we propose an indexing model named TiC-Tree, in order to simultaneously index and store multidimensional detailed and aggregated data. Our contribution exploits the temporal nature of data and focuses on range and/or group-by queries. We evaluate our proposal with the synthetic data set Star Schema Benchmark and advocate it in comparison with other existing solution.
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Ahmed, U., Tchounikine, A., Miquel, M., Servigne, S. (2010). Real-Time Temporal Data Warehouse Cubing. In: Bringas, P.G., Hameurlain, A., Quirchmayr, G. (eds) Database and Expert Systems Applications. DEXA 2010. Lecture Notes in Computer Science, vol 6262. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15251-1_12
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DOI: https://doi.org/10.1007/978-3-642-15251-1_12
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