Abstract: Data analytics is the process of analysing unprocessed data to derive conclusions. In this paper, we'll examine the trends in employee turnover and the factors that influence them. A model that can forecast whether a specific employee will leave the organisation or not will be developed. The objective is to develop or enhance various retention methods for selected staff. The paper presents data pre-processing, the initial step in data analytics. Techniques for data pre-processing transform unusable data into useful forms. Real-world data are frequently insufficient, inconsistent, and full of inaccuracies. Analysis and prediction are of higher quality when these factors are eliminated. Inference, or the process of drawing conclusions, is the main emphasis of data analytics. In this paper 2 out of top 3 strategies affecting employee turnover are being analysed and graphs plotted. The 3 top features include evaluation v/s exit, average monthly income v/s exit and satisfaction v/s exit.
Keywords: examination of raw or crude data and drawing conclusions- data analytics, employee turnover pattern, data pre-processing, evaluation v/s exit, average monthly income v/s exit and satisfaction v/s exit.
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DOI:
10.17148/IJARCCE.2023.12114
