Orclever Proceedings of Research and Development

Data Plateau: A Unified Analytics Platform with Intuitive Interfaces for Real-Time and ML-Driven Insights

Mehmet Tasan

Softtech

https://orcid.org/0009-0006-6569-3989

Yusuf Ozkan

Softtech

https://orcid.org/0009-0007-0614-1823

Ahmet Omer Ozgur

Softtech

https://orcid.org/0009-0002-0481-3693

Alper Ozpinar

Istanbul Commerce University

https://orcid.org/0000-0003-1250-5949

DOI: https://doi.org/10.56038/oprd.v4i1.457

Keywords: Generative AI, Fintech industry, self service reporting, non-expert EDA, user-centric interfaces

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Abstract

Recent advances in artificial intelligence, particularly generative AI, have significantly transformed the financial technology (fintech) industry. This paper explores the development and application of Data Plateau, an integrated data analytics platform designed to simplify complex data manipulation and analysis tasks within the fintech domain. Data Plateau empowers users with intuitive, drag-and-drop interfaces, making advanced analytics accessible to a broader range of professionals.

The research aims to accomplish three main objectives. Firstly, it investigates how user-centric interfaces can facilitate the creation and deployment of machine learning models, which are vital for adapting to the dynamic financial market. Secondly, it examines the role of real-time data streams in enhancing decision-making processes within financial environments. Finally, it explores the impact of generative AI in promoting non-expert user engagement with complex data integrations and analytics.

 

This paper details the technical background and functionalities of Data Plateau, highlighting its groundbreaking integration of cutting-edge generative AI with user-friendly interfaces. By enhancing the analytical capabilities of financial professionals and broadening access to sophisticated data manipulation tools, Data Plateau fosters a more inclusive and efficient approach to data-driven decision-making. The findings underscore the platform's potential in democratizing data science within financial services. Further research is warranted to explore the long-term impact on productivity and strategic decision-making across various sectors within the finance industry.

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