• Ms. Harika Yagadasu
• Mr. CH. Srinivasa Reddy

The existing offering process is susceptible to vulnerabilities that can negatively impact project delivery. Previous studies have extensively explored memory management issues associated with large datasets; however, these studies have not proposed solutions for problem analysis or mitigation. Additionally, there has been a lack of examination into the efficiency of the data maintenance process itself. This project aims to identify and analyze issues at each stage of the public tendering process, offering potential solutions to address or mitigate these concerns. The vendor selection process for subcontracting projects or purchasing project-related goods and services is conducted through the bidding process. Bid records contain specifications for the project or information about the goods and services to be procured. In this project, we consolidate all sensitive and large-volume data provided by various stakeholders in the bidding process. Instead of relying on traditional approaches in big data systems, we employ a divide-and-retrieve approach. A prominent issue in the bidding system is its inability to provide a comprehensive contractor database containing information about their personnel, previous works, experiences, and performance evaluations. Another significant factor to consider is the scarcity of human resources, both in terms of quantity and expertise. The project aims to address these challenges and enhance the efficiency of the public tendering process.

Large Datasets, Stakeholders, Divide-Retrieve Approach, Bidding System

"Effective Data Management Using Iterative Approach From Data Systems", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 2, page no.e323-e327, February-2024, Available :http://www.jetir.org/papers/JETIR2402446.pdf

"Effective Data Management Using Iterative Approach From Data Systems", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 2, page no. ppe323-e327, February-2024, Available at : http://www.jetir.org/papers/JETIR2402446.pdf