SAP Datasphere and SAC for a Leading Mining Company
A business data fabric and self-service analytics layer built on SAP Datasphere and SAP Analytics Cloud.
The scanning was never the problem. Ranking findings by exposure rather than by severity score made the backlog finite.
Scanning covered the IT estate and the plant-adjacent networks thoroughly, and the resulting backlog had grown past fourteen thousand open findings. Ranked by CVSS base score alone, the queue offered no way to tell an unauthenticated internet-facing weakness from a critical rating on a segmented internal service, and remediation capacity was being spent close to randomly.
Findings were re-ranked against three signals the base score does not carry: whether an attacker could actually reach the component, whether working exploit code existed and was being used, and what compromise of the component would grant access to. In parallel we agreed a remediation budget per engineering team per quarter, so security work was planned against real throughput instead of being requested against none.
The genuinely urgent set resolved to sixty-one findings, a volume the platform teams could absorb without stopping the roadmap. Internet-facing criticals now clear inside three weeks, and the total backlog fell for the first time in the programme’s history rather than growing.
A business data fabric and self-service analytics layer built on SAP Datasphere and SAP Analytics Cloud.
Insight pushed to the frontline inside S/4HANA, where the decision is actually made.