Abstract
On-Line Analytical Processing (OLAP) systems based on multidimensional databases are essential elements of decision support. However, most existing data is stored in “ordinary” relational OLTP databases, i.e., data has to be (re-) modeled as multidimensional cubes before the advantages of OLAP tools are available.
In this paper we present an approach for the automatic construction of multidimensional OLAP database schemas from existing relational OLTP databases, enabling easy OLAP design and analysis for most existing data sources. This is achieved through a set of practical and effective algorithms for discovering multidimensional schemas from relational databases. The algorithms take a wide range of available metadata into account in the discovery process, including functional and inclusion dependencies, and key and cardinality information.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Golfarelli, M., Rizzi, S., Vrdoljak, B.: Data Warehouse Design from XML Sources. In: Proc. of DOLAP, pp. 40–47 (2001)
Hall, P.A.V., Dowling, G.R.: Approximate String Matching. ACM Computing Surveys 12(4), 381–402 (1980)
Huhtala, Y., Kärkkäinen, J., Porkka, P., Toivonen, H.: Efficient Discovery of Functional and Approximate Dependencies Using Partitions. In: Proc. of ICDE, pp. 392–401 (1998)
Jensen, M.R., Holmgren, T.: Discovering Multidimensional Structure in Relational Data. Thesis Report, Department Of Computer Science, Aalborg University (2002)
Jensen, M.R., Møller, T.H., Pedersen, T.B.: Specifying OLAP Cubes On XML Data. JIIS 17(2-3), 255–280 (2001)
Jensen, F.V.: Bayesian Networks and Decision Graphs. Springer, Heidelberg (2001)
Kantola, M., Mannila, H., Räihä, K., Siirtola, H.: Discovering Functional and Inclusion Dependencies in Relational Databases. JIIS 7, 591–607 (1992)
Kimball, R.: The Data Warehouse Toolkit, 2nd edn. Wiley, Chichester (2002)
Mannila, H., Räihä, K.: Algorithms for inferring functional dependencies from relations. DKE 12(1), 83–99 (1994)
Marchi, F., Lopes, S., Petit, J.: Efficient Algorithms for Mining Inclusion Dependencies. In: Jensen, C.S., Jeffery, K., Pokorný, J., Šaltenis, S., Bertino, E., Böhm, K., Jarke, M. (eds.) EDBT 2002. LNCS, vol. 2287, pp. 464–476. Springer, Heidelberg (2002)
Niemi, T., Nummenmaa, J., Thanisch, P.: Constructing OLAP Cubes Based on Queries. In: Proc. of DOLAP, pp. 9–15 (2001)
Novelli, N., Cicchetti, R.: FUN: An Efficient Algorithm for Mining Functional and Embedded Dependencies. In: Van den Bussche, J., Vianu, V. (eds.) ICDT 2001. LNCS, vol. 1973, pp. 189–203. Springer, Heidelberg (2000)
Phipps, C., Davis, K.C.: Automating Data Warehouse Conceptual Schema Design and Evaluation. In: Proc. of DMDW, pp. 23–32 (2002)
Silberschatz, A., Korth, H., Sudarshan, S.: Database System Concepts, 4th edn. McGraw Hill, New York (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Jensen, M.R., Holmgren, T., Pedersen, T.B. (2004). Discovering Multidimensional Structure in Relational Data. In: Kambayashi, Y., Mohania, M., Wöß, W. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2004. Lecture Notes in Computer Science, vol 3181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30076-2_14
Download citation
DOI: https://doi.org/10.1007/978-3-540-30076-2_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22937-7
Online ISBN: 978-3-540-30076-2
eBook Packages: Springer Book Archive