Turkish Journal of Computer and Mathematics Education
Journal license

Journal

Turkish Journal of Computer and Mathematics Education


Volume
& Issue

Volume 11, Issue 3


Published
on


Pages

1058-1064


DOI

Article

DATA-DRIVEN HR ANALYTICS DEPLOYMENT USING DATA SCIENCE


Authors

Allaboina Manisha Yadav Affiliation:
Department of Information Technology, Sreenidhi Institute of Science and Technology, Hyderabad
and Sunil Bhutada Affiliation:
Department of Information Technology, Sreenidhi Institute of Science and Technology, Hyderabad


Abstract

HR Analytics is a way to amass and evaluate HR data and change the efficiency of an enterprise. Through developing insight and engagement, HR analytics will maybe add incredible benefit to HR decision-making for workers and organizations. In this post, we come up with an end-to-end approach to HR analytics that leads to quality data for the decisions of management. We concentrate on five inclusive issues in the HR department as part of this approach; accordingly, we present strategies that can restrict these challenges. As noted, the aggregation of several fields creates truly incipient intuitions: we then plan the data collection that could be a coalescence of data from HR, survey data, and management. In addition, we interpret the findings in such a manner that HR can make decisions based on facts and not on convictions; First by running the Resume Parser, we conduct Text Analytics, which definitely screens the resumes and potentially spares the manual efforts during recruitment; Second, we cluster the data in a Word cloud that helps to recognize talent. Additionally, to get more insight into the data, we convert the data. We translate the date of birth to age as part of transformations and wages to other preferred currency values. Next on the data collected from the employee survey, we conduct Nostalgic Analytics and later determine the main success metrics. In the end, on an interactive dashboard, we visualize the information so that HR makes the right decision based on obvious data.


Keywords

Key performance indicators, Predictive power score, Resume Parser, Sentimental Analysis, Target Variable Analysis


Citation

Yadav, A. M. & Bhutada, S. (2020). DATA-DRIVEN HR ANALYTICS DEPLOYMENT USING DATA SCIENCE. Turkish Journal of Computer and Mathematics Education, 11(3), 1058–1064.

Published by: Engineering Journals

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