CIO OPINION
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 boxticking 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 is stored securely while obsolete data is archived or deleted. All of these factors make an important contribution towards good governance.
4. Operationalise data strategy to embed it into business culture
On an operational and cultural level, businesses must focus on practical execution and ensuring that data policies, technologies, and governance frameworks translate into day-to-day operational success. Ideally, data from disparate sources will be integrated so users have a unified view that facilitates effective decisionmaking, such as the links between customer trends, inventory and finances.
With the appropriate data hardware and software systems in place, organisations can then set out the methods required to ensure data is accurate, organised and subject to proper governance. This provides a trusted foundation on which to build a data culture and where each stakeholder can be confident that the data they access and use is reliable, secure and fit for purpose. This confidence enables teams to make data-driven decisions, innovate with analytics and derive meaningful insights that support the underlying business objectives.
5. Future-proof infrastructure and processes
Data management should also be future-proof and integrate seamlessly with evolving business applications. By taking a modular approach, for example, businesses can scale specific components independently, ensuring flexibility and built-in adaptability to changing data management needs and emerging technologies.
This approach also ensures interoperability across diverse storage environments, preventing vendor lock-in and enabling businesses to adapt to future data growth without disruption. Additionally, embedding automation and AI-driven data governance can enhance operational efficiency, proactively addressing security risks and compliance requirements as the regulatory landscape inevitably evolves even further.
Each of these components shares the requirement for effective, affordable and high-performance data management technologies. With these capabilities in place, businesses can move forward with high levels of confidence in their approach to data management no matter what the future brings. p
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