Abstract
We present a functional model for the analysis of large volumes of detailed transactional data, accumulated over time. In our model, the data schema is an acyclic graph with a single root, and data analysis queries are formulated using paths starting at the root. The root models the objects of an application and the remaining nodes model attributes of the objects. Our objective is to use this model as a simple interface for the analyst to formulate queries, and then map the queries to a commercially available system for the actual evaluation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Agrawal, R., Gupta, A., Sarawagi, S.,, S.: Modelling Multi-dimensional Databases. IBM Research Report, IBM Almaden Research Center (1995)
Agrawal, R., et al.: On the computation of multidimensional aggregates. In: Proceedings 22nd International Conference on Very Large Databases (1996)
Arbor Software Corporation, Sunnyvale, CA: Multi-dimensional Analysis: Converting Corporate Data into Strategic Information. White Paper (1993)
Codd, E.F.: Providing OLAP (On-Line Analytical Processing) to User Analysts: an IT Mandate. Technical Report, E.F. Codd and Associates (1993)
Date, C.J.: An introduction to database systems, 8th edn. Addison-Wesley, Reading (2005)
Fagin, R., et al.: Multi-structural databases. In: PODS, June 13-15, 2005, Baltimore, MD (2005)
Gray, J., Bosworth, A., Layman, A., Pirahesh, H.: Data Cube: A relational aggregation operator generalizing group-by, crosstabs, and subtotals. In: Proceedings of ICDE 1996 (1996)
Gyssens, M., Lakshmanan, L.L.: A foundation for Multidimensional databases. In: Proceedings 22nd International Conference on Very Large Databases (1996)
Harinarayanan, V., Rajaraman, A., Ullman, J.D.: Implementing data cubes efficiently. SIGMOD Record 25(2), 205–227 (1996)
Kimball, R.: The data warehouse toolkit. J. Wiley and Sons, Inc., Chichester (1996)
Li, C., Wang, X.S.: A data model for supporting on-line analytical processing. In: Proceedings Conference on Information and Knowledge Management, pp. 81–88 (1996)
Ramakrishnan, R., Gehrke, J.: Database Management Systems, 3rd edn. McGraw-Hill, New York (2002)
Red Brick Systems White Paper: Star schemes and star join technology. Red Brick Systems, Los Gatos, CA (1995)
Spyratos, N.: The Partition Model: A Functional Approach. INRIA Research Report 430 (1985)
Spyratos, N.: The partition Model: A deductive database Model. ACM Transactions on Database Systems 12(1), 1–37 (1987)
Spyratos, N.: A Partition Model for Dimensional Data Analysis. LRI Research Report (2006)
Vassiliadis, P., Sellis, T.: A survey of logical models for OLAP Databases. SIGMOD Record 28(4), 64–69 (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Spyratos, N. (2006). A Functional Model for Data Analysis. In: Larsen, H.L., Pasi, G., Ortiz-Arroyo, D., Andreasen, T., Christiansen, H. (eds) Flexible Query Answering Systems. FQAS 2006. Lecture Notes in Computer Science(), vol 4027. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11766254_5
Download citation
DOI: https://doi.org/10.1007/11766254_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34638-8
Online ISBN: 978-3-540-34639-5
eBook Packages: Computer ScienceComputer Science (R0)