Continuous Intelligence: A Sea-Change in Streaming Data Processing

Organizations are drowning in streams of live data. Big-data "store-then-analyze" architectures can't store or analyze data quickly enough to deliver continuous situational insights. Data is only ephemerally useful, but it's also boundless.
Can faster/smarter databases help? There are hundreds to choose from, including on-prem, open source and cloud services. Sadly, there's a limit to how much "intelligence" one can ask of a database engine. They don't run applications and can't make sense of data. And they are typically a network hop away from application logic, so access is slow compared to the CPU and memory. This talk will introduce continuous intelligence - a new way to deal with use-cases where traditional store-then-analyze applications can't deliver insights in time. Instead, continuous intelligence addresses the need to statefully fuse streaming and traditional data, analyzing, learning, and predicting on-the-fly in response to streaming data from distributed sources concurrently, in context and at huge scale. The talk will also provide an overview of the (open source) components of a continuous intelligence application stack and demonstrate two application examples of their use.