Database modernization is facing significant challenges due to the impact of legacy systems, technical debt, and potential downtime. A recent study by Caylent, an AWS Premier Tier Services Partner, surveyed over 300 IT leaders across various industries, including manufacturing, healthcare, and entertainment, revealing the difficulties enterprises face in updating their data infrastructure.
The findings indicate that only 6% of organizations successfully complete their most challenging database migration projects on schedule, with the same percentage reporting zero downtime. Many migrations incur substantial delays, highlighted by the fact that 46% of participants noted experiencing over five hours of downtime during complex migrations. Such interruptions lead to operational slowdowns, lost revenue, and a negative customer experience as reported by 44%, 49%, and 51% of respondents, respectively.
The study identified common challenges during migration efforts, particularly with database version upgrades, cross-cloud transitions, and on-premises to cloud moves. Even though organizations pursue migrations to enhance scalability, lower licensing costs, or mitigate vendor lock-in, many underestimate the complexity involved in executing these changes.
While artificial intelligence (AI) is beginning to play a role in easing these challenges, its potential remains largely untapped. About 60% of respondents utilized generative AI or automation tools in their most difficult migration projects, and 77% found these tools helpful or highly effective. However, a significant 53% expressed uncertainty about which AI tools and capabilities were most suitable for their needs, highlighting a knowledge gap in AI adoption in data migrations.
The study pinpointed three particularly time-consuming processes in migration: transferring data to the target database, validating that database and its integrations, and adapting schemas to fit the new platform. Mismanagement of these steps can lead to errors and extended downtime.
Lori Williams, CEO of Caylent, noted that the survey reinforces the prevailing experience that modernization is essential but often hindered by legacy technical debt and outdated strategies. She suggested that integrating generative AI with expertise can enhance efficiency, reduce downtime, and decrease costs, facilitating faster migrations.
As enterprises feel increasing pressure to modernize their databases to accommodate emerging technologies, including AI and advanced analytics, these findings serve as a cautionary tale. It underscores the importance of recognizing the high risks of downtime and disruption during migration while also noting that AI-driven solutions may provide a pathway to smoother and more agile transformations.
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