Case studies on LLM centric and services oriented data analytics agent development
Conference paper
Yu, H., Sutton, J., O'Neill, S. and Reiff-Marganiec, S. 2025. Case studies on LLM centric and services oriented data analytics agent development. ICSIE '24: Proceedings of the 2024 13th International Conference on Software and Information Engineering. Derby United Kingdom 02 - 04 Dec 2024 Association for Computing Machinery. https://doi.org/10.1145/3708635.3708655
| Authors | Yu, H., Sutton, J., O'Neill, S. and Reiff-Marganiec, S. |
|---|---|
| Type | Conference paper |
| Abstract | This paper presents a novel service orchestration framework for a chatbot application focused on data analytics questions. The framework integrates Large Language Models (LLMs) with service-oriented computing to transform data analytics into a dynamic, conversational experience. The approach leverages advancements in LLM technology to enable real-time, automated data insights via chatbot interfaces, making complex data analytics accessible across various industries. In addition, the data will be processed and analysis at edge-machine rather than post all the data directly to the LLMs on the cloud. Therefore, the Central to the framework is the local Micro Analytics Service (MAS) and a dynamic service-data coordination framework, which together facilitate the decoupling of data from business logic, allowing for intuitive engagement with analytics processes. Through two case studies, retail data analysis and regional healthcare planning, the ability of the framework to provide actionable insights through natural language prompts is demonstrated, showcasing its potential to significantly reduce barriers to sophisticated data analytics. The evaluation reveals strong performance in data connection and code generation, with identified areas for improvement in visualizations and handling complex data scenarios. |
| Keywords | LLM-driven service orchestration; Dynamic data analytics services; Services Computing |
| Year | 2025 |
| Conference | ICSIE '24: Proceedings of the 2024 13th International Conference on Software and Information Engineering |
| Journal | Proceedings of the 2024 13th International Conference on Software and Information Engineering |
| Publisher | Association for Computing Machinery |
| Digital Object Identifier (DOI) | https://doi.org/10.1145/3708635.3708655 |
| Web address (URL) | https://doi.org/10.1145/3708635.3708655 |
| Publisher's version | License File Access Level Open |
| Journal citation | p. 69–76 |
| ISBN | 9798400717765 |
| Web address (URL) of conference proceedings | https://dl.acm.org/doi/proceedings/10.1145/3708635 |
| Output status | Published |
| Publication dates | |
| Online | 26 Apr 2025 |
| Publication process dates | |
| Deposited | 01 Jul 2025 |
Permalink -
https://repository.derby.ac.uk/item/qyv89/case-studies-on-llm-centric-and-services-oriented-data-analytics-agent-development
Download files
140
total views51
total downloads18
views this month2
downloads this month
Export as
Related outputs
A novel real-time battery state estimation using data-driven prognostics and health management
Pimentel, J., McEwan, A. and Yu, H. 2025. A novel real-time battery state estimation using data-driven prognostics and health management. Applied Sciences. 15 (5), pp. 1-21. https://doi.org/10.3390/app15158538Engineering critical analysis software services: A graph-RAG and self-learning large language model agent services approach
Yu, H., Scanlon, B. and Reiff-Marganiec, S. 2025. Engineering critical analysis software services: A graph-RAG and self-learning large language model agent services approach. International Conference on Service Oriented Software Engineering (IEEE SOSE 2025). Tucson, Arizona, USA 21 - 24 Jul 2025 IEEE.Impact of inter-city interactions on disease scaling
Loureiro, L.A., Neto, N.R., Sutton, J., Perc, M. and Ribeiro, R.V. 2025. Impact of inter-city interactions on disease scaling. Scientific Reports. 15 (498), pp. 1-12. https://doi.org/10.1038/s41598-024-84252-zMulti-step ahead battery SOC estimation using data-driven prognostics and health management
Pimentel, J., McEwan, A. and Yu, H. 2025. Multi-step ahead battery SOC estimation using data-driven prognostics and health management. ICSIE '24: 13th International Conference on Software and Information Engineering. Derby, United Kingdom 02 - 04 Dec 2024 ACM. https://doi.org/10.1145/3708635.3708642Density scaling laws and rural-to-urban transitions 1
Ribeiro, H. V., Sutton, J. and Hanley, Q. S. 2024. Density scaling laws and rural-to-urban transitions 1. in: D'Acci, L. S. (ed.) Urban Scaling Allometry in Urban Studies and Spatial Science Abingdon: Oxfordshire Routledge. pp. 1-13Explainable DCNN Decision Framework for Breast Lesion Classification from Ultrasound Images Based on Cancer Characteristics
AlZoubi, A., Eskandari, A., Yu, H. and Du, H. 2024. Explainable DCNN Decision Framework for Breast Lesion Classification from Ultrasound Images Based on Cancer Characteristics . Bioengineering. 11 (5), pp. 1-23. https://doi.org/10.3390/bioengineering11050453
A Heteroscedastic Bayesian Generalized Logistic Regression Model with Application to Scaling Problems
Sutton, J., Shahtahmassebi, G., Hanley, Q. S. and Ribeiro, H. V. 2024. A Heteroscedastic Bayesian Generalized Logistic Regression Model with Application to Scaling Problems. Chaos, Solitons & Fractals. 182, pp. 1-11. https://doi.org/10.1016/j.chaos.2024.114787An Experimental Study of Integrating Fine-tuned LLMs and Prompts for Enhancing Mental Health Support Chatbot System
Yu, H. and McGuinness, S. 2024. An Experimental Study of Integrating Fine-tuned LLMs and Prompts for Enhancing Mental Health Support Chatbot System. Journal of Medical Artificial Intelligence. pp. 1-16. https://doi.org/10.21037/jmai-23-1Deep Recognition of Chinese Herbal Medicines Based on a Caputo Fractional Order Convolutional Neural Network
Tao Li, Jiawei Yang, Chenxi Li, Lulu Lv, Kang Liu, Zhipeng Yuan, Youyong Li, Hongqing Yu and Yu, H. 2024. Deep Recognition of Chinese Herbal Medicines Based on a Caputo Fractional Order Convolutional Neural Network. International Workshop on Internet of Things of Big Data for Healthcare. Springer. https://doi.org/10.1007/978-3-031-52216-1_4Evaluation of Integrated XAI Frameworks for Explaining Disease Prediction Models in Healthcare
Yu, H., Adebola Alaba and Ebere Eziefuna 2024. Evaluation of Integrated XAI Frameworks for Explaining Disease Prediction Models in Healthcare. International Workshop on Internet of Things of Big Data for Healthcare. Springer. https://doi.org/10.1007/978-3-031-52216-1_2Attention Enhanced Siamese Neural Network for Face Validation
Yu, H. 2023. Attention Enhanced Siamese Neural Network for Face Validation. Artificial Intelligence and Applications. 2 (1), pp. 21-27. https://doi.org/10.47852/bonviewAIA32021018IoTBDH-2023: The 5th International Workshop on Internet of Things of Big Data for Healthcare
Qi, J., Yu, H., Yang, P., Yang, Y. and Pang, Z. 2023. IoTBDH-2023: The 5th International Workshop on Internet of Things of Big Data for Healthcare. 32nd ACM International Conference on Information and Knowledge Management (CIKM’23), Birmingham, UK. ACM. https://doi.org/10.1145/3583780.3615299AIMS: An Automatic Semantic Machine Learning Microservice Framework to Support Biomedical and Bioengineering Research
Yu, H., O'Neill, S. and Kermanizadeh, A. 2023. AIMS: An Automatic Semantic Machine Learning Microservice Framework to Support Biomedical and Bioengineering Research. Bioengineering. 10 (10), pp. 1-18. https://doi.org/10.3390/bioengineering10101134Population density and spreading of COVID- 19 in England and Wales
Sutton, J., Shahtahmassebi, G., Riberiro, H. and Hanley, Q. 2022. Population density and spreading of COVID- 19 in England and Wales. PLos ONE. 17 (3), pp. 1-19. https://doi.org/10.1371/journal.pone.0261725A unified graph model based on molecular data binning for disease subtyping
Hassan Zada, M., Yuan, B, Khan, W., Anjum, A., Reiff-Marganiec, S. and Saleem, R. 2022. A unified graph model based on molecular data binning for disease subtyping. Journal of Biomedical Informatics. pp. 1-24. https://doi.org/10.1016/j.jbi.2022.104187Learning Disease Causality Knowledge from Web of Health Data
Yu, H. and Reiff-Marganiec, S. 2022. Learning Disease Causality Knowledge from Web of Health Data. International journal on semantic web and information systems. 18 (1), pp. 1-19. https://doi.org/10.4018/IJSWIS.297145Recommender Systems Evaluator: A Framework for Evaluating the Performance of Recommender Systems
dos Santos, Paulo V.G., Tardiole Kuehne, Bruno, Batista, Bruno G., Leite, Dionisio M., Peixoto, Maycon L.M., Moreira, Edmilson Marmo and Reiff-Marganiec, Stephan 2021. Recommender Systems Evaluator: A Framework for Evaluating the Performance of Recommender Systems. in: Springer.Large-scale Data Integration Using Graph Probabilistic Dependencies (GPDs)
Zada, Muhammad Sadiq Hassan, Yuan, Bo, Anjum, Ashiq, Azad, Muhammad Ajmal, Khan, Wajahat Ali and Reiff-Marganiec, Stephan 2020. Large-scale Data Integration Using Graph Probabilistic Dependencies (GPDs). IEEE. https://doi.org/10.1109/bdcat50828.2020.00028Targeted ensemble machine classification approach for supporting IOT enabled skin disease detection
Yu, H. and Reiff-Marganiec, S. 2021. Targeted ensemble machine classification approach for supporting IOT enabled skin disease detection. IEEE Access. 9, pp. 50244-50252. https://doi.org/10.1109/ACCESS.2021.3069024Performance evaluation of machine learning techniques for fault diagnosis in vehicle fleet tracking modules
Sepulevene, Luis, Drummond, Isabela, Kuehne, Bruno Tardiole, Frinhani, Rafael, Filho, Dionisio Leite, Peixoto, Maycon, Reiff-Marganiec, Stephan and Batista, Bruno 2021. Performance evaluation of machine learning techniques for fault diagnosis in vehicle fleet tracking modules. The Computer Journal. https://doi.org/10.1093/comjnl/bxab047A repairing missing activities approach with succession relation for event logs
Liu, Jie, Xu, Jiuyun, Zhang, Ruru and Reiff-Marganiec, Stephan 2020. A repairing missing activities approach with succession relation for event logs. Knowledge and Information Systems. https://doi.org/10.1007/s10115-020-01524-6A multi-objective optimized service level agreement approach applied on a cloud computing ecosystem
Azevedo, Leonildo Jose de Melo de, Estrella, Julio C., Toledo, Claudia F. Motta and Reiff-Marganiec, Stephan 2020. A multi-objective optimized service level agreement approach applied on a cloud computing ecosystem. IEEE Access. https://doi.org/10.1109/ACCESS.2020.3006171