Middleware Event Streams Use cases
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Build responsive, engaging experiences

 A large data-driven company needs to create new ways to engage with their customers and they know that whatever solutions they provide must be highly responsive.

The challenge is that the data that will power the new offerings is locked up in back end systems and currently there are significant latency issues when retrieving such data.

Highly responsive customer solutions

Provide data through event streams Connecting IBM® Event Streams to your back-end systems and creating streams of change events addresses data inaccessibility. The first new application subscribes to these event streams to build a local view of the data. Moving data closer to the application provides customers with a highly responsive user experience.
Scale without impacting back-end systems New applications often need access to the same existing data. Because data streams have already been set up in IBM Event Streams, the new applications simply need to subscribe to these. This enables each new application to build its own view of relevant data without placing any additional load on back-end systems.
Continue your journey to cloud As companies continue their journey to the cloud, IBM Event Streams helps them replicate these streams of events to their various cloud environments. This offers the same, low latency, easy access to their business data.

Real-time data streams

A company currently maintains a data lake that they use to process their sales data. They’ve been able to gain valuable insights by analyzing their customer data, but want to use real-time data streaming to shorten the feedback loop. This will enable them to drive more real-time decisions for their data streams.

Move to a shorter, stronger feedback loop

Gain insights from historic data IBM Event Streams is used as a buffer to connect the company’s myriad data sources to their data lake. This includes click streams from their website and transactions from their sales registers. This data is then used to identify patterns, which could be used to inform future marketing campaigns.
Add in real-time data streams To identify situations in real time and take immediate action, the company writes new stream processing applications. These applications subscribe to existing topics in Event Streams, requiring no alterations to the back-end systems.
Adopt machine learning Companies often wonder if they can predict some situations before they happen. By predicting events before they unfold, the companies have more opportunities to perfectly tailor their offers to their customers’ needs.

Drive business opportunity Companies use existing data to train machine learning models. Once trained, these models can process real-time streams of data. The models provide predictions about future situations, which are used to drive further business opportunities.

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