The MarkLogic architecture being delivered in this effort supports multiple missions simultaneously, employs automated indexing, and supports at-scale concurrent querying with performance evaluation. The DF&NN ANOM intelligent system provides affordable data-driven and goal-driven real-time automated abnormality detection, characterization, event tracking, historical context reporting, multiple satellite status visualization, and event relationship discovery across multiple data sources. The operational payoff to JSpOC/JICSpOC is real-time automated satellite status to include on-orbit attack detection and anomaly attribution to support SSA.In Phase 2 MarkLogic provides the aggregation of heterogeneous data into a common data platform and DF&NN provides the increased personnel efficiency and cost reduction for SSA due to the new turnkey ANOM capability that will automatically determine when to retrain, what to retrain on, and when to promote to real-time operations for each satellite. The DF&NN intelligent systems have been proven at TRL7 to learn normal patterns of life to detect abnormal measurand correlations or temporal behavior in State of Health (SOH) telemetry, space weather, space catalog, and other data. DF&NN Smoking Gun tools discover unknown correlations amongst events from multiple sources. Abnormality Detection Classification Viewer (ADCV) provides historical context, ringer suppression, tailored event tracking, raw data strip charts, and abnormal correlation culprits.