Towards Better Data Selection for Self-Service Business Intelligence Outputs: a Local Authorities Case Study

Mathieu Lega

Towards Better Data Selection for Self-Service Business Intelligence Outputs: a Local Authorities Case Study

Research output: Contribution in Book/Catalog/Report/Conference proceeding › Conference contribution

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Original language	English
Title of host publication	Proceedings of the Doctoral Consortium Papers Presented at the 34th International Conference on Advanced Information Systems Engineering (CAiSE 2022), June 06–10, 2022, Leuven, Belgium
Publication status	Published - 2022

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DoctoralConsortiumAccepted author manuscript, 756 KB

MP: Academic research on the exploitation of local government data
Burnay, C. (PI), Castiaux, A. (PI), Dodeigne, J. (PI), Linden, I. (PI) & Jacquet, V. (Researcher)
1/01/21 → 31/12/22
Project: Research

Reducing the Effects of Information Overload on Governments Decision-Making: Empirical Frameworks to Support Data Selection
Lega, M. (Author), Burnay, C. (Supervisor), Linden, I. (Co-Supervisor), Gnabo, J.-Y. (President), Kolp, M. (Jury), Simonofski, A. (Jury) & CRUSOE, J. (Jury), 24 Apr 2024
Student thesis: Doc types › Doctor of Sciences

Cite this

@inproceedings{ce54a1b58b5b4a73ac5c936f6fb40395,

title = "Towards Better Data Selection for Self-Service Business Intelligence Outputs: a Local Authorities Case Study",

author = "Mathieu Lega",

year = "2022",

language = "English",

booktitle = "Proceedings of the Doctoral Consortium Papers Presented at the 34th International Conference on Advanced Information Systems Engineering (CAiSE 2022), June 06–10, 2022, Leuven, Belgium",

}

Towards Better Data Selection for Self-Service Business Intelligence Outputs: a Local Authorities Case Study. / Lega, Mathieu.
Proceedings of the Doctoral Consortium Papers Presented at the 34th International Conference on Advanced Information Systems Engineering (CAiSE 2022), June 06–10, 2022, Leuven, Belgium. 2022.

Research output: Contribution in Book/Catalog/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Towards Better Data Selection for Self-Service Business Intelligence Outputs

T2 - a Local Authorities Case Study

AU - Lega, Mathieu

PY - 2022

Y1 - 2022

M3 - Conference contribution

BT - Proceedings of the Doctoral Consortium Papers Presented at the 34th International Conference on Advanced Information Systems Engineering (CAiSE 2022), June 06–10, 2022, Leuven, Belgium

ER -

Towards Better Data Selection for Self-Service Business Intelligence Outputs: a Local Authorities Case Study

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Projects

MP: Academic research on the exploitation of local government data

Student theses

Reducing the Effects of Information Overload on Governments Decision-Making: Empirical Frameworks to Support Data Selection

Cite this