The Hype and Hide of Data Science-Driven Business Utilities

Abstract

Technological innovation has made emerging technologies a goldmine, with a ground for experimenting and creating big hype in the business domain. However, there are various hides too, which washed off in the presence of big hypes. As a new entrant in the data science domain, Big Data and Data Analytics have also created much noise on upscaling utility in almost all business and management domains. It would be imperative to highlight the hides and drawbacks of the emerging technologies besides praising the hypes. The objective of research work is to present a holistic view of various related technologies and their inter-linkage. Besides, identify multiple technologies present in space and originated in a recent time to hold dominance. The hype has been there, but the aim is to highlight related technologies' hides to make new entrants understand what all these about before choosing the best out of the rest, based on their compatibility to their business environment, and not on the preferences and choices. The topics and technologies in search are from the Data science domain, mainly Big Data and Analytics-related technologies, like Artificial Intelligence, Machine learning, and Deep learning, to name a few. The objective behind its formation and utilization has also been considered part of the research. It will be more to do with a systematic study based on initial interviews, search, and data collected from various users, implementers, innovators, creators, or consultants. A holistic report will be prepared and shown to understand its root ground and origin as a whole. Some frameworks and parameter-based Technological Acceptance models will be discussed to make the utility based on these parameters.