Abstract
The growing usage of data-driven decision-making has boosted the role of Database Management Systems (DBMS) in the framework of efficient business analytics. The growing big data, cloud computing, and artificial intelligence necessitate spectacular opportunities and challenges that organizations face while handling, storing, and analyzing vital information in the business. The paper discusses the modern tendencies and issues of DBMS for business analytics with regards to scalability, real-time processing, interoperability, and security. A literature search was performed in articles published between 2020 and 2025 with the aim of identifying: the existing technologies, patterns of their use, and areas of research and development. The report elucidates the importance of a growing trend towards the use of cloud-native databases, NoSQL and NewSQL databases, in-memory computing, and the use of AI to assist in query optimization as major trends that are changing the market. Although there are drawbacks like data governance, complexity in integration of data, high costs of implementation, and skills shortages, which may still pose obstacles to full adoption. The paper can add value to the literature by charting the recent developments in DBMS, discussing the essential shortcomings and providing suggestions fororganizations desiring to improve their analytics. The insights have academic and practical implications for the researchers, technology providers, and businesses looking forward to deriving a competitive advantage out of an advanced database solution.
Keywords
Database Management Systems, Business Analytics, Data Warehousing, Cloud Databases, Scalability.
Citations
IRE Journals:
Jyothi Swaroop Myneni "Trends and Challenges in Database Management Systems for Business Analytics" Iconic Research And Engineering Journals Volume 8 Issue 7 2025 Page 784-791
IEEE:
Jyothi Swaroop Myneni
"Trends and Challenges in Database Management Systems for Business Analytics" Iconic Research And Engineering Journals, 8(7)
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