Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{168455,
        author = {Santhosh Vijayabaskar},
        title = {Deep Learning for Financial Forecasting: Integrating Large Language Models with Automated Decision Systems},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {5},
        pages = {949-954},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=168455},
        abstract = {In advancement of recent era, business organization is developing drastically as there is an increase number of Information Technology (IT) as they gives wide impact on the national and international development as they all managing the vast and complex number of data. In order to analyses the performance of data, those vast data has to be processed and analysed. In managing the data, Extract, Transform and Load (DATA) process is applied and stored in the data warehouse as repository in order to take effective distributed based decision as it faces the problem of time consuming process. As the data warehouse takes the data source in the distributed manner as it is difficult to integrate those data. To overcome the above challenges, the Modified DATA based Data warehouse is proposed as it is applied with modified multi-dimensional based bottom up approach as it carried out various activities to deeply analysis the data based on content profiling. In the process of cleaning, confirming and delivery of data depends on the various data sources. Then algorithm makes three various process of data extraction as it provides data cleaning and conforming to create the conform steps based on the source data analysis using data hierarchy structure. Until the data sources gets integrated based on the various distributed database, DATA steps are performed. In the analysis, modified DATA is applied on any real time organization as it takes various source table to compare the actual and expected results. Then various metadata testing is performed on various documentation to makes the process of transformation effective.},
        keywords = {DATA process, Data extraction, IT organization, Transformation, data warehouse, distributed data.},
        month = {October},
        }