A company currently maintains a data lake which they use to process their sales data. They’ve been able to gain valuable insights by analyzing their customer data, but want to shorten the feedback loop from weeks to minutes. This will enable them to drive more real-time decisions.
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 web site 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, new stream processing applications are written.
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 further business opportunities
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.