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Cogynt: Zero code
0.29%of the world’s population
… are programmers
Process of Computational Thinking
Decomposition
Breaking big
problems into smaller
more manageable
problems
1. Abstraction
Simplify and generalize
problem to make one
solution work for
multiple problems
2.
Algorithm
Design
Step-by-step
instructions on how
to execute solution
4.3. Pattern
Recognition
Analyze and look for a
repeating sequences
Process of Computational Thinking
Decomposition
Breaking big
problems into smaller
more manageable
problems
1. Abstraction
Simplify and generalize
problem to make one
solution work for
multiple problems
2.
Algorithm
Design
Step-by-step
instructions on how
to execute solution
4.3. Pattern
Recognition
Analyze and look for a
repeating sequences
Process of Computational Thinking
Decomposition
Breaking big
problems into smaller
more manageable
problems
1. Abstraction
Simplify and generalize
problem to make one
solution work for
multiple problems
2.
Algorithm
Design
Step-by-step
instructions on how
to execute solution
4.3. Pattern
Recognition
Analyze and look for a
repeating sequences
Process of Computational Thinking
Decomposition
Breaking big
problems into smaller
more manageable
problems
1. Abstraction
Simplify and generalize
problem to make one
solution work for
multiple problems
2.
Algorithm
Design
Step-by-step
instructions on how
to execute solution
4.3. Pattern
Recognition
Analyze and look for a
repeating sequences
Process of Computational Thinking
Decomposition
Breaking big
problems into smaller
more manageable
problems
1. Abstraction
Simplify and generalize
problem to make one
solution work for
multiple problems
2.
Algorithm
Design
Step-by-step
instructions on how
to execute solution
4.3. Pattern
Recognition
Analyze and look for a
repeating sequences
Leverage humans’natural aptitude for Abstract Thinking
Decomposition
Breaking big problems into smaller more
manageable problems
1.
Abstraction
Simplify and generalize problem to make one
solution work for multiple problems
2.
Algorithm Design
Step-by-step instructions on how to execute solution4.
3. Pattern Recognition
Analyze and look for a repeating sequences
Leverage humans’natural aptitude for Abstract Thinking
Decomposition
Breaking big problems into smaller more
manageable problems
1.
Abstraction
Simplify and generalize problem to make one
solution work for multiple problems
2.
Algorithm Design
Step-by-step instructions on how to execute solution4.
3. Pattern Recognition
Analyze and look for a repeating sequences
Complex Event Processing (CEP)
E V E N T
E V E N T
E V E N T
E V E N T
W E D D I N G
C O M P L E X S O C I A L
B E H A V I O R S
Hierarchical Complex Event Processing (HCEP) in Cogynt
N - E V E N T
P A T T E R N
L A Y E R S
O B S E R V A B L E E V E N T S
P A T T E R N CP A T T E R N A P A T T E R N B
E V E N T CE V E N T BE V E N T A
E V E N T A A E V E N T B B
P A T T E R N A A P A T T E R N B B
A C T I O N A B L E
I N T E L L I G E N C E
……
I N C R E A S I N G
L E V E L S O F
A B S T R A C T I O N
P R O B L E M
D E C O N S T R U C T I O N
CEP Modeling building blocks
• Events
• Constraints
• Patterns
• Simple computations
• e.g. aggregations, logical
operations, arithmetic
CEP Modeling building blocks
• Events
• Constraints
• Patterns
• Simple computations
• e.g. aggregations, logical
operations, arithmetic
CEP Modeling building blocks
• Events
• Constraints
• Patterns
• Simple computations
• e.g. aggregations, logical
operations, arithmetic
CEP Modeling building blocks
• Events
• Constraints
• Patterns
• Simple computations
• e.g. aggregations, logical
operations, arithmetic
Example: Mobile Bank Fraud Detection
Example: Mobile Bank Fraud Detection
• Kafka Topics
bank accounts
• account_number: "GB42BTMC10820791248736"
• balance: 564000
• date_created: "1970-03-20T23:07:24.000000Z"
• first_name: "Scott"
• last_name: "Taylor”
• Contact_cell: +1 606-448-4927
bank transactions
• source_account: "GB11ZYSI67308341311527"
• dest_account: "GB05DWMH53095278548915"
• Amount: 3000
• txn_time: "2020-02-05T11:39:44.000000Z"
• txn_id: "Taylor"
Example: Mobile Bank Fraud Detection
• Kafka Topics
• Detect and notify when transfer attempt is being made to a suspected
mule account
bank accounts
• account_number: "GB42BTMC10820791248736"
• balance: 564000
• date_created: "1970-03-20T23:07:24.000000Z"
• first_name: "Scott"
• last_name: "Taylor”
• Contact_cell: +1 606-448-4927
bank transactions
• source_account: "GB11ZYSI67308341311527"
• dest_account: "GB05DWMH53095278548915"
• Amount: 3000
• txn_time: "2020-02-05T11:39:44.000000Z"
• txn_id: "Taylor"
Example: Mobile Bank Fraud Detection
• Kafka Topics
• Detect and notify when transfer attempt is being made to a suspected
mule account
1. Transfers exceed threshold amount of funds
2. Destination account is less than 24 hrs old
3. Repeated transfers to same destination account within an hour
bank accounts
• account_number: "GB42BTMC10820791248736"
• balance: 564000
• date_created: "1970-03-20T23:07:24.000000Z"
• first_name: "Scott"
• last_name: "Taylor”
• Contact_cell: +1 606-448-4927
bank transactions
• source_account: "GB11ZYSI67308341311527"
• dest_account: "GB05DWMH53095278548915"
• Amount: 3000
• txn_time: "2020-02-05T11:39:44.000000Z"
• txn_id: "Taylor"
DEMO
No-Code Development
Development Team No Coding Platform
No-Code Development
Development Team No Coding Platform
Development Time
Testing
Cost
No-Code Development
Development Team No Coding Platform
Development Time
Testing
Cost
Customizability
No-Code Development
D E V T E A M
Application x 1
Subject
Matter
Experts
Applications x 100
Thank you

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Virtual Flink Forward 2020: Cogynt: Flink without code - Samantha Chan, Aslam Tajwala

  • 2. 0.29%of the world’s population … are programmers
  • 3. Process of Computational Thinking Decomposition Breaking big problems into smaller more manageable problems 1. Abstraction Simplify and generalize problem to make one solution work for multiple problems 2. Algorithm Design Step-by-step instructions on how to execute solution 4.3. Pattern Recognition Analyze and look for a repeating sequences
  • 4. Process of Computational Thinking Decomposition Breaking big problems into smaller more manageable problems 1. Abstraction Simplify and generalize problem to make one solution work for multiple problems 2. Algorithm Design Step-by-step instructions on how to execute solution 4.3. Pattern Recognition Analyze and look for a repeating sequences
  • 5. Process of Computational Thinking Decomposition Breaking big problems into smaller more manageable problems 1. Abstraction Simplify and generalize problem to make one solution work for multiple problems 2. Algorithm Design Step-by-step instructions on how to execute solution 4.3. Pattern Recognition Analyze and look for a repeating sequences
  • 6. Process of Computational Thinking Decomposition Breaking big problems into smaller more manageable problems 1. Abstraction Simplify and generalize problem to make one solution work for multiple problems 2. Algorithm Design Step-by-step instructions on how to execute solution 4.3. Pattern Recognition Analyze and look for a repeating sequences
  • 7. Process of Computational Thinking Decomposition Breaking big problems into smaller more manageable problems 1. Abstraction Simplify and generalize problem to make one solution work for multiple problems 2. Algorithm Design Step-by-step instructions on how to execute solution 4.3. Pattern Recognition Analyze and look for a repeating sequences
  • 8. Leverage humans’natural aptitude for Abstract Thinking Decomposition Breaking big problems into smaller more manageable problems 1. Abstraction Simplify and generalize problem to make one solution work for multiple problems 2. Algorithm Design Step-by-step instructions on how to execute solution4. 3. Pattern Recognition Analyze and look for a repeating sequences
  • 9. Leverage humans’natural aptitude for Abstract Thinking Decomposition Breaking big problems into smaller more manageable problems 1. Abstraction Simplify and generalize problem to make one solution work for multiple problems 2. Algorithm Design Step-by-step instructions on how to execute solution4. 3. Pattern Recognition Analyze and look for a repeating sequences
  • 10. Complex Event Processing (CEP) E V E N T E V E N T E V E N T E V E N T W E D D I N G
  • 11. C O M P L E X S O C I A L B E H A V I O R S Hierarchical Complex Event Processing (HCEP) in Cogynt N - E V E N T P A T T E R N L A Y E R S O B S E R V A B L E E V E N T S P A T T E R N CP A T T E R N A P A T T E R N B E V E N T CE V E N T BE V E N T A E V E N T A A E V E N T B B P A T T E R N A A P A T T E R N B B A C T I O N A B L E I N T E L L I G E N C E …… I N C R E A S I N G L E V E L S O F A B S T R A C T I O N P R O B L E M D E C O N S T R U C T I O N
  • 12. CEP Modeling building blocks • Events • Constraints • Patterns • Simple computations • e.g. aggregations, logical operations, arithmetic
  • 13. CEP Modeling building blocks • Events • Constraints • Patterns • Simple computations • e.g. aggregations, logical operations, arithmetic
  • 14. CEP Modeling building blocks • Events • Constraints • Patterns • Simple computations • e.g. aggregations, logical operations, arithmetic
  • 15. CEP Modeling building blocks • Events • Constraints • Patterns • Simple computations • e.g. aggregations, logical operations, arithmetic
  • 16. Example: Mobile Bank Fraud Detection
  • 17. Example: Mobile Bank Fraud Detection • Kafka Topics bank accounts • account_number: "GB42BTMC10820791248736" • balance: 564000 • date_created: "1970-03-20T23:07:24.000000Z" • first_name: "Scott" • last_name: "Taylor” • Contact_cell: +1 606-448-4927 bank transactions • source_account: "GB11ZYSI67308341311527" • dest_account: "GB05DWMH53095278548915" • Amount: 3000 • txn_time: "2020-02-05T11:39:44.000000Z" • txn_id: "Taylor"
  • 18. Example: Mobile Bank Fraud Detection • Kafka Topics • Detect and notify when transfer attempt is being made to a suspected mule account bank accounts • account_number: "GB42BTMC10820791248736" • balance: 564000 • date_created: "1970-03-20T23:07:24.000000Z" • first_name: "Scott" • last_name: "Taylor” • Contact_cell: +1 606-448-4927 bank transactions • source_account: "GB11ZYSI67308341311527" • dest_account: "GB05DWMH53095278548915" • Amount: 3000 • txn_time: "2020-02-05T11:39:44.000000Z" • txn_id: "Taylor"
  • 19. Example: Mobile Bank Fraud Detection • Kafka Topics • Detect and notify when transfer attempt is being made to a suspected mule account 1. Transfers exceed threshold amount of funds 2. Destination account is less than 24 hrs old 3. Repeated transfers to same destination account within an hour bank accounts • account_number: "GB42BTMC10820791248736" • balance: 564000 • date_created: "1970-03-20T23:07:24.000000Z" • first_name: "Scott" • last_name: "Taylor” • Contact_cell: +1 606-448-4927 bank transactions • source_account: "GB11ZYSI67308341311527" • dest_account: "GB05DWMH53095278548915" • Amount: 3000 • txn_time: "2020-02-05T11:39:44.000000Z" • txn_id: "Taylor"
  • 20. DEMO
  • 22. No-Code Development Development Team No Coding Platform Development Time Testing Cost
  • 23. No-Code Development Development Team No Coding Platform Development Time Testing Cost Customizability
  • 24. No-Code Development D E V T E A M Application x 1 Subject Matter Experts Applications x 100