### Abstract

Original language | English |
---|---|

Title of host publication | Proceedings of the 20th International Conference on Enterprise Information Systems (ICEIS 2018) |

Place of Publication | Madeira |

Publisher | SciTePress |

Pages | 221-228 |

ISBN (Electronic) | 9789897582981 |

DOIs | |

Publication status | Published - 2018 |

Event | 20th International Conference on Information Systems - Funchal, Madeira, Portugal Duration: 21 Mar 2018 → 24 Mar 2018 |

### Conference

Conference | 20th International Conference on Information Systems |
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Abbreviated title | ICEIS 2018 |

Country | Portugal |

City | Funchal, Madeira |

Period | 21/03/18 → 24/03/18 |

### Fingerprint

### Keywords

- OLAP Databases, Business Analytics, Explanatory Analytics, Sensitivity Analysis, Decision-support Systems

### Cite this

*Proceedings of the 20th International Conference on Enterprise Information Systems (ICEIS 2018)*(pp. 221-228). Madeira: SciTePress. https://doi.org/10.5220/0006791702210228

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*Proceedings of the 20th International Conference on Enterprise Information Systems (ICEIS 2018).*SciTePress, Madeira, pp. 221-228, 20th International Conference on Information Systems, Funchal, Madeira, Portugal, 21/03/18. https://doi.org/10.5220/0006791702210228

**Sensitivity analysis in OLAP databases.** / Caron, Emiel; Daniels, Hennie.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Sensitivity analysis in OLAP databases

AU - Caron, Emiel

AU - Daniels, Hennie

PY - 2018

Y1 - 2018

N2 - The theoretical underpinnings under which sensitivity analysis is valid in OLAP databases are dealt with in this paper. Sensitivity analysis is considered to be the reverse of explanation generation in diagnostic reasoning. Our exposition differentiates between sensitivity analysis in systems of purely drill-down equation and mixed systems of equations with also business model equations. It is proven that there is an unique additive drilldown measure defined on all cubes of the aggregation lattice. This proof is the basis for sensitivity analysis in OLAP databases, where a change in some base cell in the lattice is propagated to all descendants in its upset. For sensitivity analysis in mixed systems of equations a matrix notation is presented and the conditions for solvability are discussed. Due to the fact that such systems are typically overdetermined in OLAP databases, the implicit function theorem cannot be applied. Therefore, we proposed a method to reduce the number of equations in the system and apply the implicit function theorem on a subsystem of the original system. We conclude with an alternative method for what-if analysis in mixed systems of equations.

AB - The theoretical underpinnings under which sensitivity analysis is valid in OLAP databases are dealt with in this paper. Sensitivity analysis is considered to be the reverse of explanation generation in diagnostic reasoning. Our exposition differentiates between sensitivity analysis in systems of purely drill-down equation and mixed systems of equations with also business model equations. It is proven that there is an unique additive drilldown measure defined on all cubes of the aggregation lattice. This proof is the basis for sensitivity analysis in OLAP databases, where a change in some base cell in the lattice is propagated to all descendants in its upset. For sensitivity analysis in mixed systems of equations a matrix notation is presented and the conditions for solvability are discussed. Due to the fact that such systems are typically overdetermined in OLAP databases, the implicit function theorem cannot be applied. Therefore, we proposed a method to reduce the number of equations in the system and apply the implicit function theorem on a subsystem of the original system. We conclude with an alternative method for what-if analysis in mixed systems of equations.

KW - OLAP Databases, Business Analytics, Explanatory Analytics, Sensitivity Analysis, Decision-support Systems

U2 - 10.5220/0006791702210228

DO - 10.5220/0006791702210228

M3 - Conference contribution

SP - 221

EP - 228

BT - Proceedings of the 20th International Conference on Enterprise Information Systems (ICEIS 2018)

PB - SciTePress

CY - Madeira

ER -