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Achieving Real-Time Responses with Big Data

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By: Peter Schutt | Senior Director

Organizations are moving to real-time responses and making optimal, real-time business decisions by detecting rapidly changing situations from massive volumes and various sources of data, according to new research from James Taylor, CEO of Decision Management Solutions.

These decisions range from one-off strategic decisions to monthly and weekly tactical decisions to high-volume, high-speed front-line operational decisions. Organizations now demand these front-line decisions must increasingly be made in real time.

Mobile devices, cloud computing, social media, sensors, and cameras are now ubiquitous and produce massive amounts of changing data with unprecedented contextual and geo-location information. To extract the maximum value from dynamic and perishable data, organizations need to process data much faster and take timely action. Whether marketing to customers and prospects, offering proactive support, detecting and preventing fraud, or managing the Internet of Things, real-time decision-making is indispensable and high-ROI.

Responding in real time requires systems as opposed to people to make operational decisions automatically. Agile, analytic, and adaptive Decision Management Systems combine business rules and predictive analytics to blend human intuition, company policies, and machine learning prescribe tailored recommendations for tens of millions repetitive decisions at split-second speeds. Event processing adds correlation and pattern detection on a scale of millions of events and data streams in motion at microsecond speeds.

Event-based Decision Management Systems enrich event-based data with traditional and big data sources and determine when and why a real-time response might be required. By leveraging decision engines based on business rules and analytics, Decision Management Systems can determine what the best, most effective business response for every interaction. A combination of Oracle products allows organizations to respond effectively in real time. This solution brief discusses Oracle Event Processing and Oracle Real-Time Decisions, which are at the heart of a real-time business decision solution.

There are five key elements and critical capabilities of an Event-Decision Management System for real-time responses with big data.

  1. Combine event correlation, business rules, advanced analytics, predictive analytics into a single solutions stack.
  2. Structure the pieces to act in a very heterogeneous environment to access structured data, unstructured data, traditional data sources, NoSQL, and Hadoop and in a wide variety of data formats.
  3. Ensure scalability to deploy out to the very edge of your organization to your data center and be able to mix and match the event correlation and decision-making capabilities at different points within your architecture.
  4. Empower business users with adaptability and agility to make the changes they want to the business and to learn automatically.
  5. Employ a very extensible solution to be able to add new ways to handle unpredictable events and changes.

Watch James Taylor describe the business rationale for real-time responses and the five key characteristics of
a solution.

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