Fast Data as a different approach to Big Data for managing large quantities of “in-flight” data that help organizations get a jump on those business-critical decisions. Difference between Big Data and Fast Data is comparable to the amount of time you wait downloading a movie from an online store and playing the dvd instantly.
Data Mining as a process to extract info from a data set and transform it into an understandable structure in order to deliver predictive, advanced analytics to enterprises and operational environments.
The combination of Fast Data and Data Mining are changing the “Rules”
6. Obstacles to Faster Manage Data – Latency Gap
While Ensuring Accuracy, Efficiency, and Scale
Fragmented
event entities
The Gap
Business Value
Business event
Data captured
Analysis completed
Action taken
Action Time
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Source: Richard Hackethorn’s Component’s of Action Time
7. What is Fast Data?
Turning High Velocity Data into Value
▪ It’s about getting more from in-flight data
▪ It’s about faster action, faster insights
▪ It’s about running your business in real-time
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9. Oracle Fast Data Approach
Filter, Move, Transform, Analyze, and Act at High Velocity
Network Status
In-Memory
Data Grid
FILTER &
CORRELATE
Real Time Streams
Information
• Parallel Multiple Streams: jms, files, coherence, db,..
• Different Object Type: text, java object…
• High throughput for data Aggregation and Event Querying
Coherence Data Grid holds the data and compute in parallel
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21. Fast Data Mining Demo:
Fraud Prediction in action…
▪ Extract Knowledge starting from a csv file
▪ Execute Anomaly Detection Mining on stored data
▪ Put in place a RealTime Event Processing Flow
▪ Consuming event from In-Memory Data Grid
▪ Obtain instantly Fraud Prediction from :
Streaming Data
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