Explanatory analysis in business intelligence systems

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

In this paper we describe a method for the discovery of exceptional values in business intelligence (BI) systems, in particular OLAP information systems. We also show how exceptional values can be explained by underlying causes. OLAP applications offer a support tool for business analysts and accountants in analyzing financial data because of the availability of different views and managerial reporting facilities. The purpose of the methods and algorithms presented here, is to extend OLAP based systems with more powerful analysis and reporting functions. We describe how exceptional values at any level in the data, can be automatically detected by statistical models. Secondly a generic model for diagnosis of atypical values is realized in the OLAP context. By applying it, a full explanation tree of causes at successive levels can be generated. If the tree is too large, the analyst can use appropriate filtering measures to prune the tree to a manageable size. This methodology has a wide range of applications such as interfirm comparison, analysis of sales data and the analysis of any other data that possess a multi-dimensional hierarchical structure. The method is demonstrated in a case study on financial data.
Original languageEnglish
Title of host publicationProceedings of the 20th European Conference on Information System (ECIS 2012)
EditorsB. Dinter, S. Smolnik
Place of PublicationBarcelona
PublisherUnknown Publisher
Pages77-89
Publication statusPublished - 2012

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Competitive intelligence
Sales
Information systems
Availability
Industry
Statistical Models

Cite this

Caron, E. A. M., & Daniëls, H. A. M. (2012). Explanatory analysis in business intelligence systems. In B. Dinter, & S. Smolnik (Eds.), Proceedings of the 20th European Conference on Information System (ECIS 2012) (pp. 77-89). Barcelona: Unknown Publisher.
Caron, E.A.M. ; Daniëls, H.A.M. / Explanatory analysis in business intelligence systems. Proceedings of the 20th European Conference on Information System (ECIS 2012). editor / B. Dinter ; S. Smolnik. Barcelona : Unknown Publisher, 2012. pp. 77-89
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title = "Explanatory analysis in business intelligence systems",
abstract = "In this paper we describe a method for the discovery of exceptional values in business intelligence (BI) systems, in particular OLAP information systems. We also show how exceptional values can be explained by underlying causes. OLAP applications offer a support tool for business analysts and accountants in analyzing financial data because of the availability of different views and managerial reporting facilities. The purpose of the methods and algorithms presented here, is to extend OLAP based systems with more powerful analysis and reporting functions. We describe how exceptional values at any level in the data, can be automatically detected by statistical models. Secondly a generic model for diagnosis of atypical values is realized in the OLAP context. By applying it, a full explanation tree of causes at successive levels can be generated. If the tree is too large, the analyst can use appropriate filtering measures to prune the tree to a manageable size. This methodology has a wide range of applications such as interfirm comparison, analysis of sales data and the analysis of any other data that possess a multi-dimensional hierarchical structure. The method is demonstrated in a case study on financial data.",
author = "E.A.M. Caron and H.A.M. Dani{\"e}ls",
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year = "2012",
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pages = "77--89",
editor = "B. Dinter and S. Smolnik",
booktitle = "Proceedings of the 20th European Conference on Information System (ECIS 2012)",
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Caron, EAM & Daniëls, HAM 2012, Explanatory analysis in business intelligence systems. in B Dinter & S Smolnik (eds), Proceedings of the 20th European Conference on Information System (ECIS 2012). Unknown Publisher, Barcelona, pp. 77-89.

Explanatory analysis in business intelligence systems. / Caron, E.A.M.; Daniëls, H.A.M.

Proceedings of the 20th European Conference on Information System (ECIS 2012). ed. / B. Dinter; S. Smolnik. Barcelona : Unknown Publisher, 2012. p. 77-89.

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

TY - GEN

T1 - Explanatory analysis in business intelligence systems

AU - Caron, E.A.M.

AU - Daniëls, H.A.M.

N1 - This paper was nominated for the Claudio Ciborra prize for highly original research among two other papers

PY - 2012

Y1 - 2012

N2 - In this paper we describe a method for the discovery of exceptional values in business intelligence (BI) systems, in particular OLAP information systems. We also show how exceptional values can be explained by underlying causes. OLAP applications offer a support tool for business analysts and accountants in analyzing financial data because of the availability of different views and managerial reporting facilities. The purpose of the methods and algorithms presented here, is to extend OLAP based systems with more powerful analysis and reporting functions. We describe how exceptional values at any level in the data, can be automatically detected by statistical models. Secondly a generic model for diagnosis of atypical values is realized in the OLAP context. By applying it, a full explanation tree of causes at successive levels can be generated. If the tree is too large, the analyst can use appropriate filtering measures to prune the tree to a manageable size. This methodology has a wide range of applications such as interfirm comparison, analysis of sales data and the analysis of any other data that possess a multi-dimensional hierarchical structure. The method is demonstrated in a case study on financial data.

AB - In this paper we describe a method for the discovery of exceptional values in business intelligence (BI) systems, in particular OLAP information systems. We also show how exceptional values can be explained by underlying causes. OLAP applications offer a support tool for business analysts and accountants in analyzing financial data because of the availability of different views and managerial reporting facilities. The purpose of the methods and algorithms presented here, is to extend OLAP based systems with more powerful analysis and reporting functions. We describe how exceptional values at any level in the data, can be automatically detected by statistical models. Secondly a generic model for diagnosis of atypical values is realized in the OLAP context. By applying it, a full explanation tree of causes at successive levels can be generated. If the tree is too large, the analyst can use appropriate filtering measures to prune the tree to a manageable size. This methodology has a wide range of applications such as interfirm comparison, analysis of sales data and the analysis of any other data that possess a multi-dimensional hierarchical structure. The method is demonstrated in a case study on financial data.

M3 - Conference contribution

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EP - 89

BT - Proceedings of the 20th European Conference on Information System (ECIS 2012)

A2 - Dinter, B.

A2 - Smolnik, S.

PB - Unknown Publisher

CY - Barcelona

ER -

Caron EAM, Daniëls HAM. Explanatory analysis in business intelligence systems. In Dinter B, Smolnik S, editors, Proceedings of the 20th European Conference on Information System (ECIS 2012). Barcelona: Unknown Publisher. 2012. p. 77-89