How Hybrid Data Integration Addresses Complex Data Issues
Unreliable data is a common challenge for generative AI startups. When data is dispersed across clouds, apps, and systems, quality and governance issues develop for AI models
Established data integration providers have been pressuring their clients to switch to single deployment models in recent years
Businesses have discretion over where and how they process data when they use a hybrid data integration method
HIPAA and GDPR require in-place processing to keep data within geographic or system restrictions. Hybrid data integration allows this
Hybrid data integration is essential for FinOps optimisation because it gives you more control over where and how data is processed
IBM Data Integration offers consumers flexible solutions that satisfy the expectations of the current hybrid cloud, in contrast to many competitors who promote strict, single deployment options
With its sophisticated remote engine, IBM Data Integration goes beyond hybrid by combining the strengths of managed and self-managed models
IBM is committed to changing to meet the contemporary data and integration needs of its clients