International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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The Future of Healthcare Data Governance AI-Enabled ETL Testing Frameworks on Data Warehousing Testing automation using ML, AI and NLP

Author(s) Arun Kumar Ramachandran Sumangala Devi
Country United States
Abstract The healthcare sector enhances the integration of artificial intelligence, natural language processing and machine learning in data governance for developing automation procedures. Data management offered AI-powered ETL testing with the adoption of an automation framework for resolving data governance issues . This insight promotes operational efficiency with assurance of data quality that empowers data security by ML, AI and NLP frameworks. The framework allows healthcare institutions to arrange unstructured data in effective insights into patient care and treatment procedures. Advanced analytics leads to the development of predictions on patient outcomes in treatment procedures. The automated process of ETL improves efficient information collection by NPL with the creation of predictive models in monitoring data management by ML
Keywords Machine learning, healthcare, predictive analytics, ETL, data warehousing.
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 6, Issue 5, September-October 2024
Published On 2024-10-07
Cite This The Future of Healthcare Data Governance AI-Enabled ETL Testing Frameworks on Data Warehousing Testing automation using ML, AI and NLP - Arun Kumar Ramachandran Sumangala Devi - IJFMR Volume 6, Issue 5, September-October 2024. DOI 10.36948/ijfmr.2024.v06i05.28559
DOI https://doi.org/10.36948/ijfmr.2024.v06i05.28559
Short DOI https://doi.org/g7942p
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