Those large binders filled with perforated pages striped in green and white may be long gone, but the batch job – paper report – human decision pattern remains engrained on our managerial consciousness, for better or worse.
Fortunately, this perception is changing. Real-time analytics technology is now a reality. However, even real-time analytics ends with a human decision, not with an automated decision leading to an action that changes the data in real-time.
Once we establish a fully automated feedback loop, then we take this final remaining bottleneck out of the equation, unleashing a new level of speed and performance.
Taking out this bottleneck is absolutely essential as we move from real-time analytics to streaming analytics. Rising to this challenge is cognitive computing – a way of analyzing streaming data that are multistructured, ambiguous, and in a constant state of flux.
The advantages are profound. Fraud detection and prevention, dynamic product pricing, Internet-of-Things (IoT) data analysis, electronic trading, customer promotion triggering, and compliance monitoring are some of the early examples of the power of streaming analytics – bolstered by cognitive computing to establish real-time, machine learning-based feedback loops that drive business value with no bottlenecks.
In order to play at this new level, however, we must learn new skills. Just as we’re struggling to move from batch job/report/decision thinking to real-time thinking, we must now take the next step: working with never-ending torrents of multistructured, dynamic data.
Attendees in this session will:
- Learn how real-time analytics changes the game, and how streaming analytics changes it again
- Understand the role cognitive computing plays in streaming analytics feedback loops
- Gain an appreciation for the new skills necessary to get value from streaming analytics