Also known as event stream processing, it is the analysis of large amounts of dynamic data through the use of continuous queries called event streams. These streams are triggered by a specific event that is the direct result of an action or set of actions, such as a financial transaction, equipment failure, social post, or click or some other measurable activity. Data can originate from the Internet of Things (IoT), transactions, cloud applications, web interactions, mobile devices, and machine sensors.
By using a streaming analytics platform, organizations can extract business value from data in motion, just as traditional analytics tools allow them to work with data at rest. Real-time streaming analytics helps a range of industries by uncovering opportunities and risks.
Data visualization. Focusing on the most important company information can help organizations manage their key performance indicators (KPIs) on a daily basis. Streaming data can be monitored in real-time, giving companies visibility into what's happening at every moment.
Business insights. If an anomalous business event occurs, it will be displayed first in the relevant dashboard. It can be used for network security, automatically detecting and responding to the threat itself. This is an area where anomalous behavior should be flagged immediately for investigation.
Increased competitiveness. Businesses looking to gain a competitive edge can use streaming data to identify trends and benchmark faster. In this way, they can outperform their competitors who are still using a slow batch analysis process.
Reduce preventable losses. With Stream Analytics, we can prevent or at least reduce the damage caused by events such as security breaches, manufacturing issues, customer churn, exchange crashes, and social crises.
Analyze day-to-day business operations. Streaming analytics provides organizations with the opportunity to ingest and gain instant insights from an influx of real-time data.
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