A data-led diagnostic approach helped a global payments provider identify and reduce cloud inefficiencies, embedding sustainable FinOps practices across a growing GCP estate.
Context:
As the business migrated from Teradata to Google Cloud, engineering teams were not fully equipped to redesign processes for the new environment. Without consistent cloud governance or FinOps maturity, inefficient legacy patterns were lifted into the cloud, causing widespread overprovision and overspend.
A smarter approach was needed to detect and eliminate these inefficiencies at scale, while embedding sustainable cloud optimisation practices to prevent regression.
Outcome:
$17.1M identified in annual savings from just 100 queries
$100M+ in potential savings forecast across the full cloud estate
Reduced compute waste and improved query performance
Shift from reactive cost control to always-on optimisation
Sustainable practices embedded to prevent future inefficiency
What we delivered:
Analysis of BigQuery logs to detect inefficiencies in high-volume queries
Identification of critical anti-patterns in legacy SQL processes
Deployment of automated reports to surface and validate optimisation opportunities
Hands-on engineering support to rework inefficient code into scalable best practice
Change recommendations to embed accountability, governance, and training across teams
Testimonial: “We focused on creating something that didn’t just demonstrate technical promise but delivered measurable value early. By combining our AI capability with deep operational knowledge, we built a solution grounded in the real world and scalable across the business.”
— Director of Engineering, Optima Partners
