and demand forecasting to optimize sales and reduce stockouts. Smart cities need real-time data from IoT sensors and historical analysis to manage traffic flow, optimize energy usage, enhance public safety or integration bottlenecks. By bridging the gap between data producers (databases, applications, IoT devices, logs, etc.) and data consumers (dashboards, AI/ML models, analytics engines, business applications) typically includes: Real-time data ingestion from structured, semi-structured and unstructured sources (IoT, logs, event streams). Multi-model storage optimization supporting relational, time-series, JSON, geospatial

the potential device & user base that could end up using AI technology; this includes smartphones, IOT devices, robotics, etc. Source: Weiss et al. ‘AI Index: Mapping the $4 Trillion Enterprise Impact’

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