Author(s) :

Karthika K, Y. Jayanth S, Munesh Kumar R, Nanda Reddy, Nithink

Conference Name :

International Conference on Recent Trends in Computing & Communication Technologies (ICRCCT’2K24)

Abstract :

We High Situations of request query can make it challenging for entrepreneurs to estimate business openings. Gathering and assaying data through various ways and technologies is increasingly getting a vital system for managing this query in multitudinous entrepreneurial crapshoots. This approach is constantly labeled “data driven entrepreneurship.” We explore a dynamic, data driven strategy to navigate request query in the assessment of business prospects. Our focus is on each individual’s investment portfolio, where each investment not only offers desired profits but also provides certainly about a specific requested parameter for an individual business occasion. We build a data science model that assesses request data (for ex: multimedia, finance, sports etc. …) while considering the investor’s trouble appetite, functional resources, business practices, character, investment, profits, time limits and compliance limitations. Our quantitative results show that rather than simply aiming for the topmost projected returns, entrepreneurs can choose investments that offer accurate information, trouble mitigation, or request influence according to their cash vacuity and trouble forbearance. Thanks to the power of data analysis, entrepreneurs can navigate misgivings more effectively, leading to better informed opinions regarding business openings.

No. of Downloads :

5