Maximizing Efficiency with a Database Management System

Paper Title: Maximizing Efficiency with a Database Management System

Authors Name: Bhuvaneshwari Madadi

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Author Reg. ID: TIJER_151436

Published Paper Id: TIJER2403048

Published In: Volume 11 Issue 3, March-2024

Abstract: An early attempt to computerize the manual system was with file-based systems. The majority of organizations are dealing with a sharp growth in the processing of enormous amounts of data. Consequently, it creates the challenge of collecting, storing, managing, and analyzing vast amounts of data that are stored in different formats. Currently, to overcome these challenges a more efficient software is used i.e., database management systems (DBMS). Database systems are more reliable and adaptable compared to file processing systems. Using a database management system enables developers to eliminate duplicate data and provide measures for analyzing large data sets. Instead of producing multiple versions of the similar data saved in new files for each application, data may be shared via a DBMS and is therefore more secure and maintained. This paper highlights a general idea of the changes brought about by storing and managing data and the emergence of database management systems (DBMS), which has led to a paradigm shift.

Keywords: File system, database management system (DBMS), Data models, Data abstraction, Transaction management.

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Page No: a376-a382

Country: Hanamkonda, Telangana, India

Research Area: Science and Technology

Published Paper URL: https://tijer.org/TIJER/viewpaperforall?paper=TIJER2403048

Published Paper PDF: https://tijer.org/TIJER/papers/TIJER2403048

"Maximizing Efficiency with a Database Management System", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.11, Issue 3, page no.a376-a382, March-2024, Available :https://tijer.org/TIJER/papers/TIJER2403048.pdf

ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar| ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

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