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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM28827

Enhanced Data-Driven Due Diligence for Unveiling Business Opportunities

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM28827

Volume:

8 |

2 |

Feb 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

SVP

S.V.R Vara Prasad

SV

Surarapu Vagdevi

YSSC

Yalaka Sai Sri Chandana

DSRTR

Dwarampudi Sai Ravi Teja Reddy

UMB

Uppalapati Mounika Bindu

CD

Chintala Deepika

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Abstract

This project, titled “Data-Driven Due Diligence – Unveiling Business Opportunities,” is dedicated to empowering Indian entrepreneurs in making informed financial decisions. In contrast to existing platforms with prohibitively high subscription costs, our project presents a cost-effective solution utilizing Python technologies, including Streamlit, SQLite, and Machine Learning libraries for linear regression. The web application comprises a streamlined signup/login process, an exclusive listing page for Indian entrepreneurs to input company details, and a versatile investment page accessible to both Indian and foreign entrepreneurs. Notably, SQL is employed for efficient database management. Through the strategic integration of advanced technologies and data analysis, this project equips entrepreneurs with valuable insights to optimize their investment strategies, fostering greater profitability.

KEYWORDS

Data analytics Due Diligence Data visualization Python Machine Learning SQLite.

Cite This Article

S.V.R Vara Prasad, Surarapu Vagdevi, Yalaka Sai Sri Chandana, Dwarampudi Sai Ravi Teja Reddy, Uppalapati Mounika Bindu, Chintala Deepika, "Enhanced Data-Driven Due Diligence for Unveiling Business Opportunities," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 2, Feb 2024.

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12/31/45347

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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