Dear Colleagues,

In the contemporary data-centric landscape, the integration of Big Data Analytics and Database systems is imperative for researchers and scholars operating at the Ph.D. level. Big Data, characterized by extensive and intricate datasets beyond the scope of conventional processing techniques, is categorized into structured, unstructured, and semi-structured types. Big Data Analytics involves the sophisticated analysis of these vast datasets to unveil concealed patterns, identify unfamiliar relationships, discern market trends, understand customer preferences, and derive other valuable business insights. This analytical process spans structured and unstructured data, as well as streaming and batch data, with sizes ranging from terabytes to zettabytes.

Database systems, including popular DBMSs like MySQL and PostgreSQL, interact with users and applications, facilitating data capture and analysis. These systems use standardized protocols like SQL, ODBC, or JDBC, enabling collaboration between multiple DBMSs. Categorized by the supported model, the widely used relational model, represented by SQL, has dominated since the 1980s.  Big Data Analytics and Database systems are pivotal components of modern data architecture, driving data-driven decision-making and strategic planning across diverse sectors such as healthcare, education, retail, and manufacturing. Mastery of these principles empowers researchers to leverage the potential of Big Data for enhancement, streamlining, and informed decision-making, thereby fostering corporate expansion. A comprehensive understanding of these systems is indispensable for effectively harnessing the immense potential of Big Data in research and practical applications.

We look forward to receiving your contributions.

Dr. Nur Azaliah Abu Bakar

Section Editor