Best Practices for Managing Hybrid Cloud Data Governance
The rapidly increasing adoption of hybrid cloud environments, blending on-premises and cloud-based systems, necessitates new data governance strategies to manage heightened complexities and ensure seamless operations. Effective data governance is essential to maintain consistency, security, and compliance across the varied landscapes that hybrid clouds present.
One of the fundamental themes in managing hybrid cloud data governance is the importance of a unified approach to monitoring and containerization. This facilitates data portability and ensures consistency across different platforms. Establishing a central data governance team, as proposed by Nick Elsberry from Xebia, is a crucial step. This team acts as the program’s leader by setting policies, providing tools, and educating decentralized teams. Regular engagement with senior management, through bi-monthly data governance board meetings, further boosts the program’s effectiveness.
Incorporating AI tools into data governance has emerged as a transformative strategy. These tools automate routine processes and significantly improve compliance. As noted by Ari Weil of Akamai, AI can swiftly scan and categorize data to ensure adherence to regulations like GDPR or HIPAA, thus minimizing human errors. However, integrating AI tools can be challenging, particularly if the data is disorganized or spread across various storage solutions.
The concept of a ‘data fabric’ has been gaining traction in this context. This approach unifies data management across diverse environments, ensuring visibility and control. Kevin Epstein from ClearScale emphasizes that data fabric solutions allow organizations to keep source data in its original location while making it accessible through data virtualization. This enhances both discoverability and governance, making it easier to manage data across hybrid cloud ecosystems.
Monitoring hybrid cloud environments holistically is another pivotal aspect of effective data governance. Kausik Chaudhuri of Lemongrass advocates for a unified monitoring platform that provides seamless visibility across all environments. Collaboration between IT, DevOps, and security teams ensures that monitoring tools are used effectively, transforming data into actionable insights. Epstein further suggests that keeping monitoring simple and focused helps to avoid distractions from the main objectives and ensures that important alerts are not overlooked.
The integration of legacy systems with modern data governance tools presents significant challenges but is crucial for a comprehensive governance strategy. Modern data governance systems typically require extensive metadata, which is often absent in legacy systems. Elsberry suggests addressing this integration challenge by enabling REST API capabilities and gradually updating these legacy systems.
For organizations operating on an international scale, navigating various data governance regulations is essential. Elsberry recommends conducting a thorough analysis of these regulations to extract applicable requirements and identify overlaps. Developing generic policies to address common regulatory themes, while creating specific policies for unique jurisdictional demands, can streamline compliance efforts. Compliance management tools aid in consistent monitoring and enforcement of these regulations.
In summary, managing data governance in hybrid cloud environments requires a multi-faceted approach. This strategy merges central control with decentralized execution, leverages AI for automation, uses data fabric for unified management, and integrates legacy systems with modern solutions. Regular interaction with senior management, streamlined monitoring, and an international perspective on compliance are crucial components. This comprehensive approach ensures robust, adaptable, and compliant data governance across hybrid cloud ecosystems.
