Observability analytics is vital for organizations to derive actionable insights from traditional telemetry data, such as logs, metrics, and traces, by allowing dynamic querying and connecting data points to uncover potential issues and trends. This approach helps organizations move beyond routine IT challenges to ensure compliance with key performance indicators (KPIs) and service-level agreements (SLAs) while also enabling exploratory, metrics-based, and predictive analyses that can inform business decisions and infrastructure planning. However, implementing observability analytics presents challenges, such as managing tool sprawl, creating context, and validating output, which requires careful consideration and strategies like automation, streamlined data collection, and utilizing data lakehouses. Tools like Dynatrace enhance observability analytics by offering functionalities such as data forecasting, predictive analytics, and exploratory analytics, enabling organizations to discover unknowns, understand their impact, and improve operations efficiently.