Manuscript Number : SHISRRJ122576

Synthetic Data Generation for Workforce Analytics : A Review of GANs and Differential Privacy Techniques in Human Capital Forecasting

Authors(4) :-Bamidele Samuel Adelusi, Abel Chukwuemeke Uzoka, Yewande Goodness Hassan, Favour Uche Ojika

In the rapidly evolving landscape of Human Resources (HR) analytics, the integration of synthetic data has emerged as a pivotal solution to address challenges associated with data privacy, accessibility, and scalability. Traditional HR data, often laden with sensitive personal information, poses significant barriers to comprehensive analysis due to stringent privacy regulations and ethical considerations. Synthetic data, generated through advanced algorithms, offers a viable alternative by mimicking the statistical properties of real datasets without compromising individual privacy. This paper delves into the motivations behind the adoption of synthetic data in HR analytics, explores the inherent challenges of utilizing real workforce data, and outlines the objectives and scope of employing generative techniques within privacy frameworks. By examining the significance of these methodologies, the study aims to illuminate the transformative potential of synthetic data in enhancing HR analytics while safeguarding ethical standards.

Authors and Affiliations

Bamidele Samuel Adelusi
Independent Researcher, Texas, USA
Abel Chukwuemeke Uzoka
United Parcel Service, Inc.(UPS), Parsippany, New Jersey, USA
Yewande Goodness Hassan
Casava MicroInsurance Ltd, Nigeria
Favour Uche Ojika
Independent Researcher, Minnesota, USA

Synthetic Data, HR Analytics, Data Privacy, Generative Techniques, Workforce Data Challenges

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Publication Details

Published in : Volume 6 | Issue 2 | March-April 2023
Date of Publication : 2023-03-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 134-148
Manuscript Number : SHISRRJ122576
Publisher : Shauryam Research Institute

ISSN : 2581-6306

Cite This Article :

Bamidele Samuel Adelusi, Abel Chukwuemeke Uzoka, Yewande Goodness Hassan, Favour Uche Ojika, "Synthetic Data Generation for Workforce Analytics : A Review of GANs and Differential Privacy Techniques in Human Capital Forecasting", Shodhshauryam, International Scientific Refereed Research Journal (SHISRRJ), ISSN : 2581-6306, Volume 6, Issue 2, pp.134-148, March-April.2023
URL : https://shisrrj.com/SHISRRJ122576

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