DATA & ANALYTICS
“ The emergence of modern data applications paired with the need to enable global collaboration poses an additional complex challenge to governance and security . A modern data platform allows its users to seamlessly integrate , apply and enforce the aforementioned core security and governance platform capabilities . It accelerates modern and global data applications development and enables application builders to focus on their core competencies and monetise opportunities with peace of mind .”
framework that empowers them to discover , understand and protect their heterogeneous data while leveraging it securely to collaborate internally and externally .
“ An effective , all-encompassing data governance strategy will enable organisations to store and manage personally identifiable information ( PII ) and other sensitive data securely while monitoring and protecting that data in near real-time ,” he describes . “ This includes modifications as well as new incoming sensitive data without the need to manually intervene and adjust existing secure workflows .
The future-proofing of data strategies A scalable and efficient data governance strategy must also be forward-looking . Technology is advancing rapidly , making it more challenging for organisations to keep pace with security and governance advancements . As a result , businesses must think about the foundations and frameworks that will apply to technology in the years to come .
“ Take generative AI and the emerging large language models ( LLMs ) as recent popular examples ,” Avanes says . “ Over the past few years , AI has swiftly become a crucial aspect of modern life , transforming the way we live , work and interact with each other , with many believing it will be one of the most profound technology shifts seen in our lifetimes . Organisations need to stay nimble , with a security and governance framework that can easily adapt to such innovations .”
As more businesses leverage LLMs , the models will adopt more sensitive and private data to learn from . “ However , the models are at risk of breaching or violating diverse compliance requirements . Take GDPR as an example . Once a model is trained , it will continue to use that data , with no process in place currently to have this data removed .
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