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3.1 What is Fast Data?
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Real-Time Analytics of Customer Financial Activities with Apache Flink
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- 1 Intro
- 2 1.2 Capital One Technology
- 3 2.1 Traditional Batch Analytics
- 4 2.3 Limitations of Traditional Batch Analytics
- 5 The Great Paradigm Shift - Real-Time Analytics
- 6 3.1 What is Fast Data?
- 7 3.2 Real-Time v/s Batch - Water Heater
- 8 3.3 Real-Time Analytics
- 9 3.4 Real-Time Analytics - Use Cases
- 10 What are the Drivers?
- 11 4.1 Business Drivers
- 12 4.2 Technology Drivers
- 13 4.3 Social Trends
- 14 4.4 New Industries and New Use Cases
- 15 5.1 Apache Flink as the Next Generation of Big Data Analytics
- 16 Apache Flink Stack
- 17 Business Use Case: Customer Activity Event Logs
- 18 6.2 Architecture of Customer Activity Logs
- 19 6.3 Real-Time Analytics with CAL Data
- 20 6.4 Implementation Details
- 21 6.4.2 Real-Time Alerts
- 22 6.4.3 Enrichment
- 23 6.4.4 Transformations
- 24 6.4.5 Window Aggregates - Time-based Sliding Window
- 25 6.4.5. Real-Time Index and Search
- 26 6.5 Generic Pattern Supports A Class of Use Cases
- 27 6.6 The Analytics Spectrum - Batch & Real-Time