Data federation is the process of using virtualization to have multiple databases function as a unified system to reduce costs and support agility.
One of the biggest technical challenges facing enterprises today is that they have to deal with a constantly growing multitude of applications and data sources. Further complicating matters is the fact that all of these sources have their own data models, constraints, dependencies, and other requirements.
This challenge has resulted in the increasing complexity of data integration workflows. As a result, many enterprises find themselves struggling to overcome operational siloes born of the fact that different departments use different systems that don’t work well together. In the end, sharing information becomes such a burden that each department operates in a bubble.
The rapid migration from on-premises legacy systems to cloud architectures has resulted in yet further complexity. With many businesses having adopted a multi-cloud approach to keep costs low and efficiency high, the sheer disparity of data sources has increased too. Evidently, it’s time to get things back under control.
Managing this complexity requires enterprise technology leaders to rethink the way they work with their data. To become data-driven, they need to consolidate and integrate their various data sources and govern their entire digital infrastructure as a single unit – even if their data remains physically isolated in different systems.