The global investment landscape has undergone a paradigm shift, focusing on Environmental, Social, and Governance (ESG) factors as the major determinants of financial sustainability in investment decisions worldwide. This study uses predictive modeling to analyze the complex link between ESG variables and investment decisions. Focusing on three key sectors: IT, FMCG, and BFS, the study adopts a predictive modeling approach, recognizing the distinct characteristics and challenges within each sector. The information depends on the data obtained from different places like ESG details, and previous financial performance pointers – EBITDA, EPS, ROE, and P/E for 2018 to 2022, inclusive of general investor behavior. We can do this by working with relevant sources of data together with machine learning methods which show what happens in the Indian market in terms of ESG influencing the market thus leading to sustainable investment outcomes. This article seeks to comprehend why investors may favor sustainability as opposed to their conventional monetary units.

The use of data mining to predict early employment readiness of students is gaining importance due to the expansion of data production in various industries. This study aims to address the employability issue in Middle Eastern nations by utilizing an Adaptive Neuro-Fuzzy Inference System (ANFIS) data mining technology. The experimental investigation used data from tracer studies conducted by three Jordanian universities, consisting of 22 parameters. Results showed that despite achieving an accuracy of 94% for the graduate dataset, ANFIS exhibited high complexity due to the large number of attributes used. The study has implications for selecting relevant variables and investigating multiple aspects. Data mining has various applications, including classification, clustering, regression, association rule development, and outlier analysis. As data production continues to expand, this study provides insights into the potential use of ANFIS in predicting early employment readiness of students in Middle Eastern nations.