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

Jayanna Hallur; Vedamurthy Gejjegondanahalli Yogeshappa; Jaishankar Inukonda; Vidya Rajasekhara Reddy Tetala

doi:10.36948/ijfmr.2024.v06i06.30151

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

Author(s)	Jayanna Hallur, Vedamurthy Gejjegondanahalli Yogeshappa, 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
Cite This	Enhancing Compliance and Governance through Data Consistency and Rationalization for Effective Risk Mitigation in Health Care - Jayanna Hallur, Vedamurthy Gejjegondanahalli Yogeshappa, Jaishankar Inukonda, Vidya Rajasekhara Reddy Tetala - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.30151
DOI	https://doi.org/10.36948/ijfmr.2024.v06i06.30151
Short DOI	https://doi.org/g8rd5m

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

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