Proceedings of the International Conference on Sustainable Computing and Artificial Intelligence (ICSCAI 2025)

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Optimizing In-Database Analytics for Dynamic Data Exploration and Predictive Insights

Authors
Meet Amin1, Maharshi Shukla2, *
1Department of Information Systems, Rider University, Lawrence Township, NJ, USA
2Department of Data Analytics Engineering, Northeastern University, Vancouver, Canada
*Corresponding author. Email: maharshishukla19@gmail.com
Corresponding Author
Maharshi Shukla
Available Online 28 May 2026.
DOI
10.2991/978-94-6239-674-6_6How to use a DOI?
Keywords
In-database analytics; SQL-aware predictive modeling; Dynamic model slicing; Mixture of Experts; Query-driven analytics
Abstract

Extracting actionable insights from large structured datasets is often a significant challenge in data analytics. Common practices for implementing advanced analytical models are to move data around. This limits agility and real-time exploration. This paper proposes a computing infrastructure for on-database data analytics capable of providing correct prediction models through dynamic generation in a relational database management system. Analytics solutions can be customised and deployed according to user requirements or specific data views. This scheme has undergone thorough empirical validation. As a result, complex analysis workflows have been more efficient, more accurate and more responsive. In this research, I lay a foundation to advance the in-situ data analytics paradigms within an organisation and offer agile, powerful and scalable capabilities for data-driven discovery and decision-making.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Sustainable Computing and Artificial Intelligence (ICSCAI 2025)
Series
Advances in Engineering Research
Publication Date
28 May 2026
ISBN
978-94-6239-674-6
ISSN
2352-5401
DOI
10.2991/978-94-6239-674-6_6How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Meet Amin
AU  - Maharshi Shukla
PY  - 2026
DA  - 2026/05/28
TI  - Optimizing In-Database Analytics for Dynamic Data Exploration and Predictive Insights
BT  - Proceedings of the International Conference on Sustainable Computing and Artificial Intelligence (ICSCAI 2025)
PB  - Atlantis Press
SP  - 51
EP  - 63
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6239-674-6_6
DO  - 10.2991/978-94-6239-674-6_6
ID  - Amin2026
ER  -