Decoding the Workplace & EOR: An Employee Survey Analysis by Data Science Techniques and Visualization
Kishankumar Bhimani, Khushbu Saradva

TL;DR
This study applies advanced data science and visualization techniques to analyze employee survey data, revealing insights into workplace dynamics, satisfaction, and burnout to inform management strategies.
Contribution
It introduces innovative visualization methods and comprehensive analysis of employee survey data to better understand workplace relationships and employee well-being.
Findings
Demographic insights into workforce composition
Identification of factors influencing employee satisfaction
Predictions of burnout risks
Abstract
This research study explores the new dynamics of employee-organi-zation relationships (EOR) [6] using advanced data science methodologies and presents findings through accessible visualizations. Leveraging a dataset pro-cured from a comprehensive nationwide big employee survey, this study employs innovative strategy for theoretical researcher by using our state-of-the-art visual-ization. The results present insightful visualizations encapsulating demographic analysis, workforce satisfaction, work environment scrutiny, and the employee's view via word cloud interpretations and burnout predictions. The study underscores the profound implications of data science across various management sectors, enhancing understanding of workplace dynamics and pro-moting mutual growth and satisfaction. This multifaceted approach caters to a diverse array of readers, from researchers in sociology and…
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Taxonomy
TopicsSupply Chain Resilience and Risk Management
