Abstract
Technology plays a major role in all spheres of life and higher education and health care are no exceptions. The use of big data in higher education and health care are relatively new. The dynamics of higher education is passing through a phase of rapid changes. Also, the amount of data available in this field and proper analytics can reap the benefits and highlight on future techniques to be followed in handling the complex situations arisen from pressure exerted by accrediting agencies, governments and other stake holders. Higher education is becoming more and more complex with several institutes entering into the market with more and more diversified approaches. This makes the functionalities of all institutes of higher education to revise their approaches frequently to cope up with this pressure. The educational institutes have to ensure that the quality of learning programmes is at par with that of their counterparts at the national and global level. Analysis of vast data sources generated in this connection being more often not available for analysis is a major concern. The analysis of these volumes of data plays a major role in understanding and ensuring that institutions are aware of the changes occurring everywhere and they are taking care of their social responsibilities. Due to digitization of medical records in an attempt to make them available for research and development over the past ten to fifteen years, there is a huge amount of data, which besides being voluminous are complex, diverse and temporal which is collected by healthcare stockholders. An analysis of these data could collectively help the healthcare industry to find out problems related to variability in healthcare quality and escalating healthcare expenditure. In this chapter we shall make a critical analysis of these aspects of higher education and healthcare with respect to big data analysis and make some recommendations in this direction.
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Tripathy, B.K. (2018). Big Data Applications in Health Care and Education. In: Roy, S., Samui, P., Deo, R., Ntalampiras, S. (eds) Big Data in Engineering Applications. Studies in Big Data, vol 44. Springer, Singapore. https://doi.org/10.1007/978-981-10-8476-8_11
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