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The purpose of this research is to examine career persistence and job satisfaction of beginning teachers. Design/methodology/approach – Four hundred and fifty‐one tenth grade students from a nationally representative sample, who aspired to be teachers, were examined over a ten year period regarding their career choices. Students who persisted in teaching were compared to students who did not persist with regard to job satisfaction. A job satisfaction model was tested using clusters of variables as guided by Social Cognitive Career Theory (SCCT).

Students who persisted in teaching were significantly more satisfied than both those who did not persist and those with non‐teaching careers. Beginning teachers were more satisfied with their jobs than those in other occupations. Teachers who had teaching licenses also reported being more satisfied than those who did not have licenses. The social‐contextual factors, i.e. race, socioeconomic status, teaching license, parents' education, and occupation were among the best predictors of job satisfaction. Research limitations/implications – We did not measure self‐efficacy directly. Instead, we used the separate yet highly correlated constructs, self‐concept and locus of control, to represent the self‐efficacy. For improvement, further research may use a more direct measure of self‐efficacy. Practical implications – Awareness of key factors influencing persistence in teaching career and job satisfaction identified in this study would provide school administrators with a sound basis for identifying students who are likely to persist in becoming teachers, and in retaining satisfied teachers. Originality/value – Findings of this study should assist educational administrators to better understand factors related to selection and retention of beginning teachers.

History teaches us that the glorious victory of mankind across the centuries was accomplished through the successful use of information. The gigantic progressions and rapid transformation of human societies have endorsed legitimacy of abundant data, multiple dynamic variables & critical complexities which reinforce the academia and researchers for understanding and pioneering into ‘Big Data Analytics (BDA)’. Health is one of the vibrant socio-economic variables which have correlations with other aspects of life, that is, education, poverty, income, etc. In fact, there are unending debates whether health can be a basic input for a holistic developmental process or it is the outcome of various developmental factors. BDAs are being used across various sectors of the economy. The developed nations have been yielding most feasible solutions using various forms of analysis of big data. Astronomical research has been using a large quantum of data for accomplishing various satellite projects, space technology, and numerous space missions for the astronaut. With the advent of fourth industrial revolution, the world community has been thriving toward a new age technological innovations that include artificial intelligence, machine learning, block chain technology, etc., which act a pivotal tool for BDAs. In the health sector, application of BDAs has been attempted and experimented in the developed nations which have resulted prolific and sustainable solutions to the most typical cumbersome problems. This chapter has demonstrated how BDAs can make progressive reforms in the Indian Health sector outlining the present status and emerging challenges.