by Angela Guess
Marty Loughlin recently wrote in Datanami, “Data governance has emerged to the forefront of financial services ever since this vertical became inundated with increasing and evolving regulations, penalties, and regulatory entities at the end of the last decade. Stringent compliance requirements not only mandate that organizations provide accountability for data, but traceability, provenance, and auditability as well. The most common response to these drivers is to build silos for specific regulations from the labyrinth of information management systems deployed throughout an organization, which frequently results in: Point solutions with limited life spans and viability; Different answers from different sources to the same question; Obfuscated data quality and lineage; Lack of agility for additional regulatory and business requirements.”
Loughlin continues, “Emerging technologies like semantic technology are transforming compliance and data governance to not only circumvents these issues but increases the yields from governance to affect nearly every aspect of data-driven processes throughout the enterprise. By embedding governance in both data management and business functions, organizations can transcend mere regulatory compliance to vastly improve fraud management, product development, customer 360 views, and much more. Implementing the uniform policies and practices of governance with semantic technologies ingrains them within business functions and supporting IT systems at such a granular level that well governed, trustworthy data becomes an implicit by-product of simply using data.”
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