Streaming analytics are used in myriad use cases across all industries. Many use cases can be categorized into a handful of technical scenarios, all of which generate enormous streams of operational data.
What Is Streaming Analytics?
Streaming analytics is the continuous processing and analysis of data records, typically at high volumes and at high speed, to extract actionable insights and/or generate automated alerts or actions, all in real time.
It’s a different analytic approach than batch processing; streaming analytics continuously processes small data sizes (often just a few kilobytes), while batch processing involves periodic (such as once daily) analysis of large amounts of data (up to multiple terabytes or more) aggregated via extract-transfer-load (ETL) processes.
Streaming analytics are different than BI
Traditional business intelligence (BI) and analytics tools were designed to work with batch-processed static sources, and often require data to be duplicated into data warehouses or proprietary data stores. These tools lack streaming query capabilities. Modern streaming analytics and data visualization tools enable queries on, and deliver analysis and insights from, streaming data sources.
Use cases for streaming analytics
Streaming analytics are used in myriad use cases across all industries. Many use cases can be categorized into a handful of technical scenarios, all of which generate enormous streams of operational data:
Technology requirements for streaming analytics