International Journal For Multidisciplinary Research

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

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Enhancing Compliance and Governance through Data Consistency and Rationalization for Effective Risk Mitigation in Health Care

Author(s) Jayanna Hallur, Vedamurthy Gejjegondanahalli Y, Jaishankar Inukonda, Vidya Rajasekhara Reddy Tetala
Country United States
Abstract In the era of big data, you absolutely must have consistency across your different data systems to make effective decision-making, be compliance, enhanced governance and security and also mitigation of risks,, and even have system integrity. The data consistency and how rationalization techniques help overcome challenges when working with heterogeneous data sources, is what this paper explores. Rationalization allows businesses to keep their data accurate and consistent by standardizing data formats, reducing duplications, measuring the data growth, categories the data sources, farmats, and aligning conflicting information. We compare the different methods of normalization, data deduplication, Master Data Management (MDM) and data integration framework. We also delve into the part that automation, artificial intelligence and machine learning play in optimizing these processes and provide scalable solutions that can potentially simplify the complexity of modern-day data environments. Practical implications from rationalization effort case studies are shown from sectors like, healthcare, finance, and e-commerce. Our specific findings show that long-term data consistency requires a systematic approach that employs technology and strong governance. In the end, this paper gives a blueprint for how to exploit rationalization methods to exploit the capabilities of data-driven insights fully.
Keywords Artificial intelligence, Compliance, Data consistency, Data deduplication, Data governance, Data integration, Data Normalization, Data rationalization, Machine learning, Master data management (MDM), Risk Mitigation
Field Computer > Data / Information
Published In Volume 6, Issue 6, November-December 2024
Published On 2024-11-13
DOI https://doi.org/10.36948/ijfmr.2024.v06i06.30151
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E-ISSN 2582-2160
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CrossRef DOI prefix of IJFMR is 10.36948/ijfmr

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