C H E Q U I N G O U T scalable storage infrastructure required to pursue data-centric objectives . This functionality must be delivered in a way that scales with changing requirements without the need for wholesale technology updates or unexpected costs .
C H E Q U I N G O U T scalable storage infrastructure required to pursue data-centric objectives . This functionality must be delivered in a way that scales with changing requirements without the need for wholesale technology updates or unexpected costs .
2 . Leverage AI and automation
Looking at AI more closely , it can be applied to various critical requirements . First , effective data management is essential to ensure GenAI models can deliver accurate and meaningful insights . Organisations that fail to focus on this crucial facet of AI development risk falling foul of the classic ‘ garbage in , garbage out ’ scenario that was a feature of early computer programming and still remains valid to this day .
Secondly , AI and automation themselves play a key role in optimising data management by enabling businesses to implement automated rules around data access , retention and movement in line with compliance and security policies . AI-powered data governance also reduces the risk of manual human errors , and instead ensures consistency and compliance across all data operations .
3 . Implement robust data governance and compliance policies
Businesses tend to view compliance in one of three ways . Some consider it as little more than a box-ticking exercise to
avoid penalties , others view it as a risk management strategy to protect data and reduce security threats , while some utilise compliance to build a competitive advantage that fosters trust and drives innovation .
But whatever the perspective , regulatory compliance is now non-negotiable . Organisations must maintain structured policies to align with various domestic and international rules , with authorities better armed than ever to impose painful sanctions when breaches occur .
From ensuring proper data documentation and access controls to retention practices , best practice also hinges on continuous monitoring and auditing of stored data . Businesses should also be in a position to categorise data based on value , risk and relevance , ensuring that critical data
Carl D ’ Halluin , CTO , Datadobi
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