The Planning OLAP Model - A Multidimensional Model with Planning Support

  • Bernhard Jaecksch
  • Wolfgang Lehner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6862)


A wealth of multidimensional OLAP models has been suggested in the past, tackling various problems of modeling multidimensional data. However, all of these models focus on navigational and query operators for grouping, selection and aggregation. We argue that planning functionality is, next to reporting and analysis, an important part of OLAP in many businesses and as such should be represented as part of a multidimensional model. Navigational operators are not enough for planning, instead new factual data is created or existing data is changed. To our knowledge we are the first to suggest a multidimensional model with support for planning. Because the main data entities of a typical multidimensional model are used both by planning and reporting, we concentrate on the extension of an existing model, where we add a set of novel operators that support an extensive set of typical planning functions.


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  1. 1.
    Agrawal, R., Gupta, A., Sarawagi, S.: Modeling Multidimensional Databases. In: Proc. of 13th. Int. Conf. on Data Engineering ICDE, vol. 7, p. 11 (1997),
  2. 2.
    Box, G., Jenkins, G.: Time Series Analysis: Forecasting and Control (1970)Google Scholar
  3. 3.
    Cabibbo, L., Torlone, R.: Querying Multidimensional Databases. In: Database Programming Languages, pp. 319–335. Springer, Heidelberg (1998), CrossRefGoogle Scholar
  4. 4.
    Codd, E., Codd, S., Salley, C.: Providing OLAP (On-Line Analytical Processing) to User-Analysis: An IT Mandate (1993),
  5. 5.
    Datta, A.: The Cube Data Model: a Conceptual Model and Algebra for On-line Analytical Processing in Data Warehouses. Decision Support Systems 27(3), 289–301 (1999), CrossRefGoogle Scholar
  6. 6.
    Gray, J., Bosworth, A., Layman, A., Pirahesh, H.: Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Total. In: ICDE, pp. 152–159 (1996)Google Scholar
  7. 7.
    Gyssens, M., Lakshmanan, L.V.S.: A Foundation for Multi-Dimensional Databases. In: Proceedings of the International Conference on Very Large Data Bases, pp. 106–115. Citeseer (1997),
  8. 8.
    Lehner, W.: Modeling Large Scale OLAP Scenarios. In: Advances in Database TechnologyâĂŤEDBT 1998, p. 153 (1998),
  9. 9.
    Li, C., Wang, X.S.: A Data Model for Supporting On-Line Analytical Processing. In: Proceedings of the Fifth International Conference on Information and Knowledge Management - CIKM 1996, vol. 199, pp. 81–88 (1996),
  10. 10.
    Ozsoyoglu, G., Ozsoyoglu, Z., Mata, F.: A Language and a Physical Organization Technique for Summary Tables. In: Proceedings of the 1985 ACM SIGMOD International Conference on Management of Data, pp. 3–16. ACM, New York (1985), CrossRefGoogle Scholar
  11. 11.
    Pedersen, T., Jensen, C., Dyreson, C.: A Foundation for Capturing and Querying Complex Multidimensional Data. Information Systems 26(5), 383–423 (2001), CrossRefMATHGoogle Scholar
  12. 12.
  13. 13.
    Vassiliadis, P.: Modeling Multidimensional Databases, Cubes and Cube Operations. In: Proceedings of Tenth International Conference on Scientific and Statistical Database Management (Cat. No.98TB100243), pp. 53–62 (1998),
  14. 14.
    Vassiliadis, P., Sellis, T.: A Survey on Logical Models for OLAP Databases. SIGMOD Record 28, 64–69 (1999)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Bernhard Jaecksch
    • 1
  • Wolfgang Lehner
    • 1
  1. 1.Database Technology GroupTU Dresden, Institute for System ArchitectureDresdenGermany

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