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This document reviews the state of the art in schema matching, focusing on large scale automatic schema matching and integration for data interoperability, discussing various techniques, application
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New challenges in data refer to the emerging issues and obstacles that organizations face when collecting, storing, analyzing, and utilizing data in the ever-evolving digital landscape.
Organizations and individuals who handle and manage data are responsible for identifying and addressing new challenges in data.
Filling out new challenges in data involves conducting comprehensive assessments, identifying potential risks and vulnerabilities, and implementing proactive strategies to overcome those challenges.
The purpose of addressing new challenges in data is to ensure data integrity, security, and compliance while maximizing the opportunities and value derived from data-driven insights.
The specific information required to be reported on new challenges in data may vary depending on the regulatory requirements and organizational policies. However, it generally involves detailing the nature of the challenge, potential impact, mitigation strategies, and progress in addressing the challenge.
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