As organizations expand into multicloud environments, they face heightened complexity in managing security, which complicates vulnerability management throughout the software development lifecycle (SDLC). Many Chief Information Security Officers (CISOs) express concerns about the increasing difficulty of vulnerability management due to complex supply chains and cloud ecosystems, with team silos and point solutions contributing to vulnerabilities slipping into production. To address these challenges, organizations are adopting security analytics, which combines data collection, aggregation, and analysis to detect potential threats early, enhance compliance, and provide improved insights and visibility across diverse IT environments. Unlike traditional Security Information and Event Management (SIEM) tools, security analytics focuses on behavior-based analysis and real-time data to proactively protect against threats. However, the implementation of security analytics faces obstacles, such as managing distributed data sources and ensuring observability for comprehensive threat analysis and response. Platforms like Dynatrace's Grail lakehouse offer solutions by integrating data lakes and warehouses to enhance security analytics capabilities, providing significant benefits through unified observability and real-time insights, ultimately improving an organization's risk posture and efficiency.