Abstract
Although nearly all data warehouses store sequential data, i.e. data with a logical or temporal ordering, traditional data warehouse or OLAP approaches fail when it comes to analyze those sequences. In this paper we will present a novel approach which generates query-specific subcubes, i.e. subcubes that consist only of data which fulfill a given sequential query pattern. These subcubes may then be analyzed using standard OLAP tools. Our approach consists of two functions which both return such subcubes. Hence, the user can still use all the well-known OLAP operations like drill-down, roll-up, slice, etc. to analyze the cube. Furthermore, this approach may be applied to all data warehousing architectures.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Bębel, B., Morzy, M., Morzy, T., Królikowski, Z., Wrembel, R.: Olap-like analysis of time point-based sequential data. In: Castano, S., Vassiliadis, P., Lakshmanan, L.V., Lee, M.L. (eds.) ER 2012 Workshops 2012. LNCS, vol. 7518, pp. 153–161. Springer, Heidelberg (2012)
Chandra, R., Segev, A.: Managing Temporal Financial Data in an Extensible Database. In: VLDB (1992)
Chui, C., Kao, B., Lo, E., Cheung, D.: S-OLAP: an OLAP System for Analyzing Sequence Data. In: SIGMOD (June 2010)
Chui, C., Lo, E., Kao, B., Ho, W.: Supporting Ranking Pattern-Based Aggregate Queries in Sequence Data Cubes. In: CIKM (2009)
Eder, J., Olivotto, G.E., Gruber, W.: A Data Warehouse for Workflow Logs. In: Han, Y., Tai, S., Wikarski, D. (eds.) EDCIS 2002. LNCS, vol. 2480, pp. 1–15. Springer, Heidelberg (2002)
Kimball, R.: The Data Warehouse Toolkit, 2nd edn. John Wiley & Sons (1996)
Koncilia, C.: The COMET Temporal Data Warehouse (PhD). In: UMI (2002)
Liu, M., Rundensteiner, E., Greenfield, K., Gupta, C., Wang, S., Ari, I., Mehta, A.: E-cube: Multi-dimensional event sequences processing using concept and pattern hierarchies. In: ICDE (2010)
Lo, E., Kao, B., Ho, W., Lee, S., Chui, C., Cheung, D.: OLAP on Sequence Data. In: SIGMOD (June 2008)
Segev, A., Shoshani, A.: Logical Modeling of Temporal Data. In: SIGMOD (1987)
Seshadri, P., Livny, M., Ramakrishnan, R.: Sequence query processing. In: SIGMOD (1994)
Seshadri, P., Livny, M., Ramakrishnan, R.: The Design and Implementation of a Sequence Database System. In: VLDB (1996)
van der Aalst, W., ter Hofstede, A., Kiepuszewski, B., Barros, A.: Workflow patterns. In: Distributed and Parallel Databases (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Koncilia, C., Eder, J., Morzy, T. (2014). Analyzing Sequential Data in Standard OLAP Architectures. In: Manolopoulos, Y., Trajcevski, G., Kon-Popovska, M. (eds) Advances in Databases and Information Systems. ADBIS 2014. Lecture Notes in Computer Science, vol 8716. Springer, Cham. https://doi.org/10.1007/978-3-319-10933-6_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-10933-6_5
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10932-9
Online ISBN: 978-3-319-10933-6
eBook Packages: Computer ScienceComputer Science (R0)