DIGITAL TRANSFORMATION
Pulling data from and maintaining data stored in legacy systems is just as critical – often, they still hold valuable information about your business. Organisations are working across hybrid landscapes with on-premises systems, multiple cloud platforms and sprawling application ecosystems. That has already made it difficult to keep data pipelines unified, but with the growth in AI capabilities, the cycles of change are faster than ever. A process that once took months to complete now changes in a matter of days.
AI models are also evolving, new protocols are emerging and industry specific models are experiencing a rise, so over time, fundamental system changes will be required for best fit.
Also, analytics engines will be adjusted and automated processes may need to be reconfigured almost overnight. Against this backdrop, data pipelines must act like a flywheel. They must be easy to change and update without breaking governance and security. Otherwise, technical debt will mount quickly.
The real challenge is not just managing the environment – it’ s adapting quickly enough to keep pace with AI-driven change while protecting your valuable company data. technologymagazine. com 167