Complex Event Processing

1. Complex Event Processing

2. Remember This? • 50 million people affected • Nuclear power plants in New York and Ohio shut down • Air traffic was slowed as flights were halted

3. Why? • Electric Power Research Institute (EPRI) White Paper Findings: • Lack of understanding of VAR reserves in the region and the adjacent regions, coupled with the possibility ofinadequate dynamic VAR support available from generators. (VAR is shorthand for reactive power, which is the additional power required for maintaining voltage stability when serving certain kinds of load, such as motors, air conditioning, and fluorescent lights.) • Insufficient “visibility” of power flow conditions over the entire region, coupled withinadequate coordination, control and communication of the power system on a regional basis. That information is flowing from 27 distribution feeds, eight re-closure or safety switches and 4,192 transformers. • Insufficient understanding of the potential impact on August 14, 2003 of newpower flow patterns caused by increased wholesale power transfers resulting from industry restructuring. • Lack of real-time regional and interconnection-wide power flow models for anticipating changing flow patterns and theformation of new bottlenecks.

4. Enterprise 2.0 (’80s – 2000) Enterprise 1.0 (’60s – ’80s) Enterprise 3.0 (2000 – 2020) Data Processing Predictive Client Server ESB Mainframe Database Building Block N-Tier 2-Tier 3-Tier Software Event Driven Batch Online Velocity 000,000,000,000’s 000’s 000,000’s Interactions

5. Enterprise 2.0 (’80s – 2000) Enterprise 1.0 (’60s – ’80s) Enterprise 3.0 (2000 – 2020) Half Life of Data Amount of Data Time to React Data Processing Predictive Client Server ESB Mainframe Database Building Block N-Tier 2-Tier 3-Tier Software Event Driven Batch Online Velocity 000,000,000,000’s 000,000’s 000,000,000’s Interactions

6. The Data Advantage Threats & Opportunities Events Enterprise 3.0 Transactions Enterprise 2.0

7. Understanding The Event Cloud Enterprise Events

8. CEP • Deriving Value from Events Value Enterprise Events

9. Result Measured Root Cause Determined Corrective Decision Made Action Taken CEP enables More Effective Decisions Business Automation  Enables Fast Response Dynamic Business Conditions Point of Transaction Response to Dynamic Conditions Effective Real-time Decisions Business Event Potential Business Value Action time

10. Using Real Time Events = A Better Way to Fly Agenda • Overview and vision for Complex Event Processing • Real-time customer problems and solutions • TIBCO BusinessEvents capabilities • Answer your questions

11. BusinessProcessManagement • BusinessOptimization • Service-OrientedArchitecture Complex Event Processing (CEP): Premises Problem There is always a “Plan”. It Never Goes According to the “Plan”. A “Pattern of Events” is an indicator of “opportunities” (inventory re-allocations). A “Pattern of Events” is an indicator of “threats” (fraud, inventory shortages). A “Pattern of Events” can be reactive situations. A “Pattern of Events” can be predictive (early warning) situations. Solution CEP is the foundation technology for detecting patterns in real-time event streams correlated with historical data.

12. 5 seconds 30 seconds 10 seconds 5 minutes 15 minutes Mail… express… fax… e-mail 20 seconds 1 hour 1 hour 1 day 1 day Velocity drives need for Event Processing Business Cycle-Time Improvements Perform Trading Analytics 30 minutes 20 minutes Airline Operations Handle Call Center Inquiries 8 hours Track Financial/Risk Position 1 day Supply Chain Updates 1 day Document Transfer 3 days Phone/Service Activation 3 days Refresh Data Warehouse 1 month Settle Trade/Transaction 5 days Build-to-Order Product 6 weeks Source: Gartner

13. Operational Intelligence in Transport & Logistics 13

14. Aircraft Communications and Operations Airport Operations Schedule Planning Aircraft Maintenance Early Alert System Context-based Decisions in Operations Aircraft Operations Dispatch, Weather Crew Management

15. Events driving Airline Scenarios • March Madness Example • An abnormally large number of “no shows” in one day could mean a mass of extras tomorrow • Station alerting for passenger patterns, monitor check-in patterns and no-show rate • Flow Rates in/out of airport • Only X aircraft getting out of airport, but Y>X aircraft are arriving there • Prevent/avoid gridlock, compare gate and off-gate parking capacities + numbers of passengers transferring to which flights

16. The Goal: Total Situational Awareness Require: • Better visibility into aircraft operations across all stations • Apply rules to all inputs and report situations that are out of tolerance • Display alerts in a meaningful way to inform not confuse Motivation:

17. ODS Services CST Services EDW Services Data Services Optimizers & Solvers Aircraft Communications and Operations Enterprise Messaging Enterprise Integration Operational Data Customer Data Enterprise Data Warehouse Other Data Complex Event Processing Solution Dispatch, Weather TIBCO BusinessEvents Match events & rules

18. Results 18

19. Union Pacific Railways - Challenges • Pre-existing Business Challenges: • Less than half of all network schedules achieved. • Track velocity = 17 mph. Goal is 20 mph; every increase in 1 mph = $10 million saving to the bottom line (each month!). • Customers over-schedule and use crews unwisely. • Appear at capacity but a system of over-schedule.

20. Union Pacific Railways - Benefits • Maintenance & Crew Management • Outsourcer instantly knows where to deliver new crews • Automatically exchange locomotive maintenance order, fulfilment and invoicing data with service providers and business partners • Trains run 1/8th mile per hour faster! • Way Side Detection • Real-time Alerting of wayside diagnostic alerts • Service Enabled Maintenance System • Pro-actively fix wheels with faulty bearings

21. TIBCO BusinessEvents v5.0 ®The 5th Generation Event Platform

22. BusinessEvents - Overview BE is a framework for messaging based intelligent, distributed agents 2. REASON Define rules of behavior to reason on a pattern of objects, events and time Rules Patterns 4. SITUATION Visualize Predictive Enterprise Actions 3. INFER Actions 1. SENSE Ability to listen to events and gather data on demand. Events Objects

23. NewOrder NewOrder Condition /TimeEvent NewOrder BusinessEvents: State-Oriented CEP Behavior Event Bus or Source Low-latency reliable Message delivery State Model Event and Data Model For Information Modeling Temporal Model For Determining Time-Dependent Information State 1 State 2 Pattern Detection Model For Recognizing Patterns and Defining Actions History and Cache

24. Concept Model Stateful object modelling. Easily visualize object relationships.

25. State Model / Process Flow UML-Compliant state model. State diagram / flow diagram is simple to follow and maintain.

26. NewOrder NewOrder (Lots ofEvents) NewOrder BusinessEvents: Rule-Oriented CEP Behavior Event Bus or Source Low-latency reliable Message delivery Rule Complex Patterns Event and Data Model For Information Modeling Temporal Model For Determining Time-Dependent Information Reaction Pattern Detection Model For Recognizing Patterns and Defining Actions History and Cache

27. Inference Rule Features High Performance Pattern Matching Large catalogue of functions built in.

28. Decision Manager Features • Rules managed in a decision-table interface. • Export/import to and from Excel.

29. NewOrder NewOrder (Lots ofEvents) NewOrder BusinessEvents: Query-Oriented CEP Behavior Event Bus or Source Low-latency reliable Message delivery Query Complex Query Event and Data Model For Information Modeling Temporal Model For Determining Time-Dependent Information Results Event Pattern Detection Model For Recognizing Patterns and Defining Actions History and Cache

30. Query CEP Agent Features • Common query language • Based on SQL/OQL • Familiar to SQL users. • Defined dynamically or statically. • API similar in structure to JDBC. select city, count(*) from LoanApp{policy: maintain last 7 days where amount > 350000} group by city

31. BE Views • Provides visibility into real-time business events • Empowers users to make effective real-time decisions and appropriate actions on critical opportunities and issues.

32. TIBCO BusinessEvents Thematic Summary events TIBCO BusinessEvents Pattern Detection Decisions Processesand Views Complex Event Processing(CEP, ESP) Decision Management(business rules) Straight Thru Processing(real-time process eventing) Real-timeDashboards(real-time Inter-active BI)

33. Application to SITS

34. Enterprise 2.0 in Action

35. Enterprise 3.0 • It's so smart that it knew there was a power outage in one neighborhood 34 minutes before the first resident called the utility. • It's so smart that the number of customer-voltage complaints — about either surges or drops — went from 70 to zero. • It's so smart that it identified a transformer that was overloaded and needed to be replaced — before it got fried. • In the past, the utility knew to replace transformers when they blew and lights went out. • The next step: to collect and share information with about 25,000 homes and businesses that have installed or will install "smart meters.“

36. Sample Event Processing Usage Summary • Adaptive Marketing • Pattern: Capture opportunity with customer while ‘the window is open’. • Telco • SLA (Service Assurance) • Real Time Service Offers and Analytics • Finance • Fraud Detection • Track and Trace Trades/Deals/Settlements • Pre/Post trade exceptions • Logistics - Track & Trace • Track Packages against a “Plan”. Infer package delays in a proactive manner. Alert customers. • Government • Track and Analyze ‘patterns’ that were otherwise very difficult to detect • Dynamic Resource Scheduling • Real Time Optimization of Resources against a “Plan”.

37. Next Steps • Email us to receive High Consequence Architecture White Paper • For more information  or to arrange a meeting to discuss your business problem  contact Atif Chaughtai achaught@tibco.com (301) 213 6708

38. Questions?