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Open-Source LLM Integrated Data Analysis Assistant with Tableau

Buşra Sabak1,
Erhan Alasar2
1Metric Yazılım Danışmanlık
2Metric Yazılım Danışmanlık
Published:December 31, 2025
DOI: 10.56038/oprd.v7i1.703
Vol. 7, No. 1 · pp. 64–74

Abstract

In corporate data analysis processes, the ability for users to perform data querying and data analysis using natural language, without needing technical knowledge, has become a critical requirement, especially for mid and senior-level managers. This study proposes a solution that offers natural language interaction in TR/EN languages and meets internal data security requirements. The platform connects to Tableau data sources through open-source LLM integration and communicates with data sources published in Tableau via the VDS API to provide real-time analysis and predictions. The architecture also has the flexibility to be integrated with cloud-native AI services in the future. The solution, with its self-service ease of use, enables data analysts and decision-makers to obtain rapid insights without having to worry about technical details.

Keywords
Real Time Data AnalysisLarge Language ModelsCloud-NativeArtificial IntelligenceTableau Integrated

References

  1. 1.Acharjya, D. P., & Kauser, A. P. (2016). A Survey on Big Data Analytics: Challenges, OpenResearch Issues and Tools. International Journal of Advanced Computer Science and Applications, 7(2), 511-518.
  2. 2.Alghamdi, N. A., & Al-Baity, H. H. (2022). Augmented Analytics Driven by AI: A Digital Transformation beyond Business Intelligence. Sensors, 22(20).
  3. 3.Gad-Elrab, A. A. (2021). Modern Business Intelligence: Big Data Analytics and Artificial Intelligence for Creating the Data-Driven Value. E-Business - Higher Education and Intelligence Applications. içinde
  4. 4.Guo, Y., Shi, D., Guo, M., Wu, Y., Chen, Q., & Cao, N. (2023). Talk2Data: A Natural Language Interface for Exploratory Visual Analysis via Question Decomposition. https://arxiv.org/abs/2107.14420 adresinden alındıLink
  5. 5.Klisarova-Belcheva, S., Ilieva, G., & Yankova, T. (2017). Business Intelligence and Analytics – Contemporary System Model. Trakia Journal of Sciences, 15, 98-304,. doi:doi:10.15547/tjs.2017.s.01.053DOI
  6. 6.Morton, K., Bunker, R., Mackinley, J., Morton, R., & Stolte, C. (2012). Dynamic Workload Driven Data Integration in Tableau. SIGMOD'12.
  7. 7.Pinheiro, J., Victorio, W., Nascimento, E., Seabra, A., Izquierdo, Y., García, G., . . . Casanova, M. (2023). On the Construction of Database Interfaces Based on Large Language Models. Proceedings of the 19th International Conference on Web Information Systems and Technologies (WEBIST 2023), (s. 373-380). doi:10.5220/0012204000003584DOI
  8. 8.Shen, L., Shen, E., Luo, Y., Yang, X., Hu, X., Zhang, X., . . . Wang, J. (2021). Towards Natural Language Interfaces for Data Visualization: A Survey. IEEE Transactions on Visualization and Computer Graphics, 29, 3121-3144.
  9. 9.Tableau Community. (2019). Sample - Superstore Sales (Excel). https://community.tableau.com/s/question/0D54T00000CWeX8SAL/sample-superstore-sales-excelxls adresinden alındıLink
  10. 10.Thanasas, G. L., & Kampiotis, G. (2024). The role of Big Data Analytics in Financial Decision-Making and Strategic Accounting. Technium Business and Management, 10, 17-33.
  11. 11.Zhang, J., Zhang, H., Chakravarti, R., Hu, Y., Ng, P., Katsifodimos, A., . . . Halevy, A. (2025). CoddLLM: Empowering Large Language Models for Data Analytics. https://arxiv.org/abs/2502.00329 adresinden alındıLink
  12. 12.M. J. Baeth and M. Aktas, “On the detection of information pollution and violation of copyrights in the social web,” Proc. IEEE SOCA, 2015.
  13. 13.M. B. Çatalkaya, O. Kalıpsız, M. S. Aktaş, and U. O. Turgut, “Data feature selection methods on distributed big data processing platforms,” in Proc. UBMK, 2018.
  14. 14.A. Mollaoğlu, G. Baltaoğlu, E. Çakır, and M. S. Aktaş, “Fraud detection on streaming customer behavior data with unsupervised learning methods,” in Proc. ICECCO, 2021.
  15. 15.B. Yildiz, “Efficient text classification with deep learning on imbalanced data improved with better distribution,” Turk. J. Sci. Technol., vol. 17, no. 1, pp. 89–98, 2022.
  16. 16.D. Bakır, M. S. Aktaş, and B. Yıldız, “A model-based evaluation metric for question answering systems,” Int. J. Softw. Eng. Knowl. Eng., vol. 35, no. 2, pp. 243–262, 2025.
  17. 17.M. S. Çiftlikçi, Y. Çakmak, T. A. Kalaycı, F. Abut, M. F. Akay, and M. Kızıldağ, “A New Large Language Model for Attribute Extraction in E-Commerce Product Categorization,” Electronics, vol. 14, no. 10, 1930, 2025.
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Cite This Article
Sabak, B., Alasar, E. (2025). Open-Source LLM Integrated Data Analysis Assistant with Tableau. *Orclever Proceedings of Research and Development*, 7(1), 64-74. https://doi.org/10.56038/oprd.v7i1.703

Bibliographic Info

JournalOrclever Proceedings of Research and Development
Volume7
Issue1
Pages64–74
PublishedDecember 31, 2025
eISSN2980-020X