About the Journal

ISCSITR - International Journal of Data Engineering (ISCSITR-IJDE) is a distinguished open-access, peer-reviewed journal, published by the International Society for Computer Science and Information Technology Research (ISCSITR). As a platform committed to advancing the field of data engineering, ISCSITR-IJDE focuses on fostering the exchange of high-quality research and innovations among global researchers, academicians, and practitioners in the field. The journal’s open-access nature ensures that the published research is accessible to a broad audience, contributing significantly to knowledge dissemination and application within both academic and industrial circles.

Aim

The primary aim of the International Journal of Data Engineering is to drive forward the frontiers of data engineering by encouraging the development and sharing of cutting-edge research. The journal seeks to bridge the divide between theoretical research and practical applications, promoting a comprehensive understanding of how new data engineering techniques and methodologies can be effectively deployed in diverse contexts. Through its rigorous review process, ISCSITR-IJDE is dedicated to maintaining high standards of academic integrity, ensuring that only impactful, innovative, and well-validated research reaches its readership.

Scope

ISCSITR-IJDE covers a wide spectrum of topics within the field of data engineering, encompassing both foundational theories and applied methodologies. The journal invites submissions on the following key areas:

  • Data Warehousing and Database Systems: Research on advancements in the design, optimization, and management of data storage solutions, focusing on scalability and performance.
  • Data Mining and Machine Learning: Contributions related to algorithmic developments and the application of machine learning models in extracting meaningful insights from data.
  • Big Data Processing and Analytics: Studies addressing challenges in handling large datasets, including frameworks and techniques for real-time processing, analytics, and visualization.
  • Data Integration and Interoperability: Research exploring methods for combining disparate data sources and ensuring seamless data interoperability to improve information synthesis and usability.
  • Data Security and Privacy: Investigations into the safeguarding of data assets through robust security protocols, encryption methods, and privacy-preserving techniques.
  • Cloud Computing and Distributed Data Systems: Papers on managing data across cloud infrastructures and distributed networks, optimizing for reliability and accessibility.
  • Data Quality and Data Governance: Analysis of frameworks for ensuring the accuracy, reliability, and governance of data assets in enterprise and research settings.

The journal also encourages interdisciplinary studies that combine data engineering with emerging fields, such as artificial intelligence, bioinformatics, and cybersecurity, recognizing that the applications of data engineering are increasingly diverse.

Audience and Contribution

ISCSITR-IJDE serves as an invaluable resource for academic researchers, industry professionals, policy-makers, and students, offering insights that can drive both theoretical advances and real-world applications. By focusing on timely and relevant topics in data engineering, ISCSITR-IJDE contributes to the broader understanding and development of data-centric technologies that support decision-making across industries. As an open-access publication, the journal’s commitment to accessible knowledge strengthens its role in facilitating progress in the data engineering community and beyond.