dom introduction-website-v1.0

1. COGILITY SOFTWARE The Leader In Model Driven Complex Event Processing
DOM Introduction
August,2009
Matthew Ghourdjian
Yngvar D. Tronstad
1
2010 Cogility Software CorporationAll Rights Reserved.Proprietary and Confidential.

2. Problem Domain

Enterprise Challenges:

3. Frequent, unpredictable and fast-changing events 4. A multitude of entities and systems requiring integration 5. Large enterprises with urgent decision support requirements between echelons 6. Integrated support of the edge-users 7. Loosely coupled organizational and technical infrastructure 8. Technical Challenges: 9. Chaotic stovepipes of uncoordinatedservices, processes and information 10. Redundant functions and services 11. Lacking coordination, interoperability and agility 12. Exploiting new technologies (e.g., web services) 13. Predicting the impact of change 14. Dealing with multi-dimensional COMPLEXITY.

Click to edit Master text styles

15. Second level 16. Third level 17. Fourth level 18. Fifth level2
19. Problem space and challenge with P-2-P integration
.
sales
support
billing
in the past, complex point-to-point integrations were used to construct an end-to-end business process
The disadvantages:

interface complexity

20. inability to quickly modify processes following initial implementation 21. expensive to maintain and extend customer
care
inventory control
shipping
3
22. Organization with overlapping functions and data
.

23. Second level 24. Third level 25. Fourth level 26. Fifth levelHorizontal: Process Oriented
Vertical: Application Oriented
4
27. Pair matching DoesntScale
.

28. Second level 29. Third level 30. Fourth level 31. Fifth level5
32. As is situation is a significant barrier
.

33. Second level 34. Third level 35. Fourth level 36. Fifth levelTraditional waterfall process
R 1.0

Long development time

37. Highrisk and development cost 38. Inflexible and difficult to change 39. High cost of failure 40. Late visibility of project successP2P Architecture
6
41. Changes in enterpriseprojects
.
35%
30%
25%
20%
%Change or creep in requirements
15%
10%
5%
10
100
10000
1000
Project size measured in FPs http://www.wikipedia.org/wiki/FP_(complexity)

Large projects will have change rates / requirement creep of > 33%

42. Medium sized projectshave change rates around 25 %Change in scope and / or requirements are inevitable
7
43. Requires a Copernican shift
.
In the beginning
We had it all wrong
Data
Apps
Apps
Apps
Apps
8
44. Requires a Copernican shift
.
Apps
Data
Apps
Apps
Put the smarts in the data watch what happens
9
45. Cogility composite application development solution

Cogility is the unique provider of an IDE that employs a fully instantiated MDA environment for creating complex, service oriented and event-driven composite applications that solve difficult problems with process execution, web service orchestration and data synchronization simultaneously

.
Process orchestration with: UML+ WS
Data Integration with: UML+ CWM
MDA+ EDA+SOA
10
46. Process oriented data synchronization
.

To simplify the design process:

47. the business process models are built by the system analysts 48. the data models and transformations are developed by the application developers 49. during the execution the reusable data transformations are executed as an integral part of the business process logic (processes + data)cogility studio enables collaboration between experts and application developers
11
50. Joint Data Integration Strategy
DIM
DIM
DIM
DIM
DIM
Layers of

Isolation

51. IndirectionDIM
DIM
DIM
Layers of
Abstraction
DIM
DIMz
DIM
DIM
MIM
d2m
m2d
Watch
List
Emerge
US Visit
IHRT
.
12
52. UML
Reusable CWM- Based Transforms
Master Information Model (MIM)
UML
UML
UML
UML
UML
CWM
UML
UML
Distinct Information Model (DIM) representing Enterprise Applications
UML
star schema data modeling with transformations
.

Eachapplication to be integrated is modeledindependently

53. The CommonViewofthe data is alsocreated as a separate model 54. Transformationsconvert data betweentheindividual systems and thecentralcorporateview13
55. UML
Reusable CWM- Based Transforms
Master Information Model (MIM)
UML
UML
UML
UML
UML
CWM
JMS/WS
Based Messaging
Layer for triggering transformations and state machines and
sending notifications
UML
UML
Distinct Information Model (DIM) representing Enterprise Applications
UML
An example of a transformation chain
.

A Separate layerconvertsincomingmessages to a common format.

56. ChainsofTransformationsexecutetogether to move data betweenapplications.14
57. Using Dom transformation for information exchange
.
Cogility Manager
JMS
JMS
JMS
MasInt
BioMetrics
Master
Information
Model
JMS
IWS
HumInt
WS
JMS
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58. Process oriented data synchronization
.
WS
Request
JMS
Message
Cogility Manager
Case
Obj
internet
M2E
Conv
HME
WS
Logic
S1
JMS
Message
S2
internet
internet
Remote
WS2
Remote
WS1
16
59. Example Cogility Solution
.
internet
External Web Applications
IPB Planning
Internal Web Applications
Suspicious Activity
TTP
Notification
Analysis
Actions
Cogility Modeler
Cogility Manager
Cogility Insight
JMSOWS
UML
Process Model
CWM Data Transx
Enterprise Reporting & Monitoring
IWS
Java ,Message Service (JMS) / Inbound Webservice (IWS) / Outbound Webservice (OWS)
GCCS
Afatds
CIDNE
C-IED
JDE
MASINT
Biometrics
Humint
Known
Association
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60. To-be transformation is required
.
R 1.0
Traditional waterfall process

Long development time

61. Highrisk and development cost 62. Inflexible and difficult to change 63. High cost of failure 64. Late visibility of project successTransx strategy
P2P Architecture
18
65. To-be transformation RESULT
.
19
66. Our Solution Approach

The overall approach to developing the Signature Analysis System using Cogility is based on an Incremental and Iterative Development (IID) approach based on simply iterating over the following key steps:

67. Information Modelling 68. Interfaces to the Environment Definition 69. System Intent and Behaviour Definition 70. Automated completeness and consistency checking 71. Auto-deployment to the staging and production environment for acceptance testing 72. Model directly executed, with real time Monitoring.
information defines the vocabulary and
persistent data structure of the system
information
adaptive
feedback
Interfaces
interfaces define the channels of communication with the outside world
cogility
methodology
iterate
behavior
rt insight
behavior specifies the business process and logic executed in terms of the information model when an interface is invoked.

The Iterative and Incremental Development (IID) is a strategy where the system grows incrementally with new features, iteration by iterations:

73. Each iteration includes production quality solution 74. Each iteration is a subset of a final system 75. Incremental and hot updates 76. Provides Early Risk reduction20
77. Typical wind tunnel plan
.
product decision
dev demo
Kick - off
alpha
demo
final demo
weeks
12
11
10
9
4
3
2
1
8
7
6
5
Phase ii Planning
productization
Decision
requirements
Initial F&F
the evolving model becomes the defined system
solution threads
Exe
Model
auto deploy
test /demo
eval
linked to evolving

demo releases

78. client capabilities 79. risk reductionfinal demo
adaptive feed-back
Exe
Model
auto deploy
test /demo
eval
COI opportunity
to the
direction
alpha demo
adaptive feed-back
Each Iterative and Incremental Model Evolution follow the same structure:
Exe
Model
auto deploy
test /demo
eval
development
21
80. Transformation issues
.
22
81. Overall benefits

Speed- 2 Development and Deployment

82. Agile and dynamic processes 83. Rapid modifications 84. Improved data integration 85. Composable services 86. Layered architecture 87. Improved asset management 88. Business Transformation 89. Incremental and iterative 90. Reduce cost of stovepipes 91. Remove bottlenecks through an end to end process focus 92. Process oriented data synchronization 93. Rapid response to changes 94. Customer experience 95. Dynamic data driven user portal 96. Shared access to information 97. Dynamic human-in-the loop interaction 98. Role based collaboration and access control 99. Architectural leadership 100. Greater agility and flexibility by introducing MDA 101. Best practices with separation of concern and layers of isolation 102. Directly executable models with built in scalability and reliability 103. MDA + SOA + EDA 23
104. Cogilitys MDA solution in summary

Binds technology and business processes

105. Simplifies the development process 106. Focuses on the solution, not the build 107. Rapid iterative development 108. Reduce risk and cost24
109. Contact information
.
Matt Ghourdjian
CEO
Cogility Software Corp
[email protected]
949.202.9877
Yngvar Tronstad
Chief Scientist,
Cogility Software Corp
[email protected]
650.450.6364
www.cogility.com
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dom introduction-website-v1.0

Technology

data models

data watch

commonviewofthe data

reusable data transformations

process orchestration

process execution

process orientedvertical

business process models