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A complete guide to the Data‑as‑a‑Service model and its role in analytics, AI, and digital transformation.
Data as a Service (DaaS) is a cloud-based model where organizations provide data on demand to users, systems, or applications through APIs, subscriptions, or platforms.
Definition
DaaS is a service model in which data is delivered, accessed, or consumed over the cloud—similar to SaaS—enabling organizations to use high-quality, ready-to-integrate data without managing physical storage or infrastructure.
As businesses increasingly depend on data for decision‑making, DaaS provides a scalable and cost‑efficient way to access external or internal datasets. Rather than investing in infrastructure, companies subscribe to data feeds or APIs.
Use cases include fraud detection data streams, real-time weather data, market data APIs, location intelligence, customer enrichment datasets, and AI‑ready training data.
DaaS also supports interoperability, as organizations integrate data across systems without large engineering overhead.
No—SaaS delivers software, whereas DaaS delivers data.
Fintechs, marketers, AI teams, product teams, researchers, and enterprises.
Yes—vendors often clean, normalize, and enrich data.