Technology leaders are seeking to modernize their data infrastructure to ensure their businesses can profit from a new era of AI-driven growth and innovation.
But Foundry’s AI Priorities Study found that only 34% agree their organization has the right data and technology in place to enable effective AI.1
Part of that challenge involves the migration of legacy data systems to cloud environments. In a CIO.com roundtable event supported by EPAM and Google Cloud, technology experts gathered to dissect how to chart a path to success in this complex but critical area.
Key topics discussed included selecting the right approach for cloud adoption, clear migration outcomes and risk mitigation during large-scale migrations.
Here are some highlights from the debate that covered six broad areas.
1) Data modernization: a strategic imperative
The roundtable started by examining how the ability to leverage modern data infrastructure has become a key competitive differentiator.
Participants acknowledged the advantages of the cloud, including reduced licensing fees, increased flexibility, improved scalability and advanced capabilities in data analytics and AI. However, the CIOs in the room also acknowledged that data migration involves substantial complexities, especially in the case of legacy databases.
2) The challenges of legacy migration
Participants debated the challenges of migrating legacy relational databases. These systems often contain decades-old data and complex, embedded server-side business logic. Documentation is often limited, and many organizations lack the internal expertise required to address these issues effectively.
Participants shared their experiences and agreed that the starting point for migration must include a comprehensive assessment of the data landscape and legacy-related dependencies.
3. Managing Total Cost of Ownership (TCO)
Managing and accelerating cloud adoption was a key topic of discussion, with participants exploring strategies to optimize the migration process while controlling costs.
The round table also covered cost management strategies, such as rightsizing cloud resources to avoid overprovisioning, leveraging cloud-native services to reduce operational overhead, and implementing robust monitoring tools to track usage and costs in real time.
4. Ensuring Continuity and Risk Mitigation
Data mobility during large-scale migrations was another significant challenge. To mitigate risks, some organizations have employed a hybrid approach, maintaining a parallel on-premises system while gradually shifting workloads to the cloud.
This approach provides a safety net and allows for incremental progress. Others have focused on improving data governance practices and enhancing data quality measures to reduce migration-related risks.
5. Partnering with external experts
Here, participants identified the key factors that drive the selection process: the need to find partners with a track record in similar migrations and the availability of flexible engagement models that align with the client’s needs.
6. Regulation, governance and compliance
The regulatory aspects of data migration and cloud adoption are also seen as a key challenge. Compliance with industry standards, data privacy laws, and specific regulatory requirements was highlighted as a critical consideration.
Organizations must ensure that data sovereignty is maintained, data is securely transferred, and appropriate controls are in place to protect sensitive information. Establishing robust data governance frameworks and embedding compliance into the design phase of migration projects were cited as effective practices.
Conclusion
This CIO roundtable offered valuable insights on navigating the challenge of data modernization. While it can be challenging, it presents a variety of opportunities for much-improved data management, cloud-native operations and advanced analytics.
Learn more about EPAM’S partnership with Google Cloud.
1AI Priorities Study https://foundryco.com/tools-for-marketers/research-ai-priorities/