Agentic AI System for Ensuring Reliability in Survey Data Analytics
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| Natura: | Recurso digital |
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Zenodo
2025
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| _version_ | 1866902032532635648 |
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| author | C.Dharani, B.Nathiya, S.Samyugtha |
| author_facet | C.Dharani, B.Nathiya, S.Samyugtha |
| contents | <div>Agentic Artificial Intelligence has emerged as a transformative approach for ensuring the reliability of survey data analytics. An intelligent platform is developed that leverages autonomous AI agents and large language models to detect and correct errors such as missing values, duplicates, outliers, and inconsistent responses within demographic survey datasets. The system integrates automated data cleaning, statistical analysis, natural language processing, and predictive modeling, with every transformation logged to maintain transparency and reproducibility. Comprehensive reports and visualizations are generated to provide actionable insights, enabling faster and more accurate decision-making. By moving beyond traditional manual and rule-based methods, the proposed framework reduces human effort, improves scalability, and enhances trust in survey-based findings. The results highlight its potential to deliver robust, efficient, and reliable analytics across domains including research, healthcare, business, and governance.</div> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17431602 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Agentic AI System for Ensuring Reliability in Survey Data Analytics C.Dharani, B.Nathiya, S.Samyugtha <div>Agentic Artificial Intelligence has emerged as a transformative approach for ensuring the reliability of survey data analytics. An intelligent platform is developed that leverages autonomous AI agents and large language models to detect and correct errors such as missing values, duplicates, outliers, and inconsistent responses within demographic survey datasets. The system integrates automated data cleaning, statistical analysis, natural language processing, and predictive modeling, with every transformation logged to maintain transparency and reproducibility. Comprehensive reports and visualizations are generated to provide actionable insights, enabling faster and more accurate decision-making. By moving beyond traditional manual and rule-based methods, the proposed framework reduces human effort, improves scalability, and enhances trust in survey-based findings. The results highlight its potential to deliver robust, efficient, and reliable analytics across domains including research, healthcare, business, and governance.</div> |
| title | Agentic AI System for Ensuring Reliability in Survey Data Analytics |
| url | https://doi.org/10.5281/zenodo.17431602 |