← Back to case studies
DataOps
Stabilising a critical monthly data process
Context
The monthly run of a critical data engine was already automated, but it carried recurring failures and pain points that required manual intervention and put important deliveries at risk.
My role
Owner of the design, planning and documentation of the execution schedules in Control-M.
Decisions and actions
I am redesigning the execution chains to run autonomously and without friction, rolling out the changes in phases so as not to compromise a complex system that is already live.
Result
The process is moving toward an unattended, stable monthly run: each phase removes points of failure while keeping the service running.
Learning
In a critical, complex system, moving in phases is what lets you improve without breaking what already works.
Want to talk about your project?
Get in touch