Data streaming is rapidly becoming the norm in modern data architectures. This can be from stream-enabled applications, or through the capabilities of Oracle GoldenGate to stream changes made to the database in realtime to targets including Kafka. This availability of data streams offers great potential and advances in the analytics world, enabling business insight to be realised sooner, and actions taken on the data whilst it is still current. Oracle Stream Analytics (OSA) brings this insight into "Fast Data" to business users through an intuitive web interface. It enables them to filter and analyse data as it arrives, including with predefined algorithms and spatial technology.
In this presentation I will present a live demonstration of how to filter, transform, and analyse streaming data with Oracle Stream Analytics from sources including Kafka. Using Oracle GoldenGate we will see how to stream individual changes from the database made by applications that were not even written with streaming capabilities. How OSA is deployed will be discussed, including its use with Spark as the runtime engine. We will also consider OSA's place in the broader analytics architecture alongside Oracle Data Integrator.