Research article · 2026
INTEGRATING BIG DATA ANALYTICS INTO DATABASE MANAGEMENT SYSTEMS FOR INTELLIGENT DATA-DRIVEN DECISION-MAKING: CHALLENGES, OPPORTUNITIES, AND EMERGING TRENDS
Abstract
Purpose: In this paper, the changing role of Database Management Systems (DBMS) for supporting big data applications and analytics and the challenges and opportunities of embedding such advanced analytics for intelligent decision making is examined. Design/Methodology/Approach: To assess the latest advancements in modern database architectures and analytics, a narrative review of literature in the field was performed, which was published primarily between 2020 and 2026. Findings: While some new technologies offer greater scalability and analytical power, traditional DBMS technologies continue to be vital for transaction processing, even if they present implementation and skills challenges, data governance, cybersecurity and legacy integration issues. Implications: Big data enables businesses to gain valuable insights, however, the implementation of hybrid and AI-powered databases, data governance, and upskilling employees will maximize the benefits of big data analytics. Originality/Value: The paper offers a holistic and up-to-date overview of modern DBMS and big data analytics and identifies new database technologies as key enablers of intelligent decision making.
Keywords
Database Management Systems (DBMS); Big Data Analytics; Data-Driven Decision-Making; Cloud Databases; Artificial Intelligence; Data Integration.
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