The challenges included critical gaps in database security and visibility across applications and data flows, a lack of automated user profiling, inconsistent policy enforcement, distributed global data with limited control, and the growing need to secure sensitive partner and business information across diverse systems and cloud environments.

The goal was to secure critical business data and ensure compliance through an automated framework, enhance threat detection and response capabilities, centralize visibility with consistent policy enforcement across platforms and focus remediation efforts on high-risk users and activities.

Leveraged automated data discovery, near-real-time monitoring with ML analytics and dynamic risk scoring to identify and mitigate risks to vendor and supply-chain data. It ensured broad platform compatibility across diverse systems and centralized visibility, utilizing Universal Connectors to seamlessly aggregate audit logs from cloud and on-premises sources, thereby enabling comprehensive and scalable security and control.

Automated discovery/classification combined with near-real-time UEBA/ML monitoring gave the client consolidated visibility and stronger protection for sensitive vendor, supplier and product data across SGXaaS and cloud native platforms. Regular vulnerability assessments and prioritized remediation reduced security gaps across databases, data warehouses and big-data environments. Achieved faster detection and response, lower audit overhead, improved regulatory readiness and a scalable security foundation to support future modernization.