Personnel Data Management System for Workforce Analytics

Marcin Pilat

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Paper

Personnel Data Management System for Workforce Analytics

Topics: Modelling & Simulation Workforce Analytics

In Proceedings of the 12th International Conference on Operations Research and Enterprise Systems - Volume 1: WAPAT, 281-287, 2023 , Lisbon, Portugal

Author: Marcin Pilat

Affiliation: Director General Military Personnel Research and Analysis, Department of National Defence, 101 Colonel By Drive, Ottawa, ON, K1A 0K2, Canada

Keyword(s): Workforce Analytics, Personnel, Data Management System, Data Mart, Dimensional Modelling.

Abstract: An effective analytics solution relies on the right data and the right data management system. We present a data management system for personnel data that is specifically designed to enable efficient workforce analytics. The system is designed using dimensional modelling and implemented as a collection of star schemas over the business functions of workforce planning, recruitment, and retention. Special internal processing during the Extract, Transform, Load process streamlines the generation of the internal data tables.

CC BY-NC-ND 4.0

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Paper citation in several formats:

Pilat, M. (2023). Personnel Data Management System for Workforce Analytics. In Proceedings of the 12th International Conference on Operations Research and Enterprise Systems - WAPAT; ISBN 978-989-758-627-9; ISSN 2184-4372, SciTePress, pages 281-287. DOI: 10.5220/0011919500003396

@conference{wapat23,
author={Marcin Pilat.},
title={Personnel Data Management System for Workforce Analytics},
booktitle={Proceedings of the 12th International Conference on Operations Research and Enterprise Systems - WAPAT},
year={2023},
pages={281-287},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011919500003396},
isbn={978-989-758-627-9},
issn={2184-4372},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Operations Research and Enterprise Systems - WAPAT
TI - Personnel Data Management System for Workforce Analytics
SN - 978-989-758-627-9
IS - 2184-4372
AU - Pilat, M.
PY - 2023
SP - 281
EP - 287
DO - 10.5220/0011919500003396
PB - SciTePress