1. H. A. El‐Ghareeb
Information Systems Dept.
If i S D
Faculty of Computers and Information Systems
Mansoura University
helghareeb@mans.edu.eg

16. Agenda
g
What is Integration ?
What are Integration Levels ?
Wh I i L l ?
What are Integration Techniques ?
What is Software Architecture ?
How can SW Architectures fit Integration Techniques?
Process Level Integration and Service Oriented
Architecture

17. What is Integration?
g
Enterprises consume more than one application.
Each application can perform its own tasks with no
E h li i f i k i h
need for others (Vice Versa: Interoperability).
Vice Versa: Interoperability).
That doesn’t mean apps do not need to know others
Th d ’ d d k h
exist (Vice Versa: Integration
Vice Versa: Integration).
Example:
E l
Updating Customer Billing address in finance system
requires updating her/his billing address in CRM.
i d i h /hi billi dd i CRM

18. Integration Levels
g
Process
Application
Data

19. Integration Techniques
g q
Integration
Techniques
Software
Data Based
Based
Database,
Standard Data Standard
Middleware
Element Enterprise
Data
Definition wide software
Warehouse
Multi-
Point To Point
Applications

20. Software Architecture
The sum of the nontrivial modules processes, and
sum nontrivial modules, processes
data of the system their structure and exact
of the system, their structure
structure
relationships to each other, how they can be and are
expected to be extended and modified and on which
extended modified, and on which
modified
technologies they depend, from which one can deduce
the exact capabilities and flexibilities of the system,
p y ,
and from which one can form a plan for the
implementation or modification of the system.

21. Common Software Architecture
Common Software Architecture
Patterns
Data Flow Control Flow
• Model‐View‐Controller • Call And Return a.k.a. Main program And
Subroutines
• Presentation‐Abstraction‐Control
• Implicit Invocation a.k.a. Event Based
• Pipe‐And‐Filter
• Manager Model
• Layered Systems
• Emulated Parallel
• Microkernel
• Client‐Server
• Repository
• Blackboard
• Finite State Machine
• Process Control
• Multi Agent System
• Broker
• Master‐Slave
• Interpreter
• Message Broker
• Message Bus
• Structural Model
• Peer‐to‐peer

22. Integration Levels
g
Process
Application
Data

23. Integration Techniques
g q
Integration
Techniques
Software
Data Based
Based
Database,
Standard Data Standard
Middleware
Element Enterprise
Data
Definition wide software
Warehouse
Multi-
Point To Point
Applications

24. Pipe And Filter Architecture
p
Pump
p Filter Filter Sink
Pipe Pipe Pipe

25. Data Based Integration Techniques
g q
Standard Data Element Definition
Driving Forces
• Easier Exchange of Data
• Reduced Development Time
• Reduced Maintainance Costs
Restraining Forces
• Costs to Develop standards definitions
• Costs to change existing systems
• Existing data definitions are different
• Some definitions need to be different
• Products use different data definitions
• Lack of industry standard definitions
• Mergers and acquistions

26. Integration Techniques
g q
Integration
Techniques
Software
Data Based
Based
Database,
Standard Data Standard
Middleware
Element Enterprise
Data
Definition wide software
Warehouse
Multi-
Point To Point
Applications

27. Repository Software Architecture
p y
Repository
Knowledge Knowledge Knowledge
Source Source Source

28. Database Integration Techniques
b i hi
Databases
Data warehouse
Driving Forces
• Easier access to enterprise wide data
• Reduced development time
• Reduced i t
R d d maintenance costs t
• Minimal effect on operational system
• use of business intelligence software
Restraining Forces
• Costs of development
• Different semantics in data sources
iff i id
• Semantic translation
• Lack of industry standard definitions
• Deciding what data to warehouse
• Delays in getting data to the warehouse
y g g
• Redundancy of data
• Data quality issues
• Brittleness of fixed record exchanges
• Performance Tuning

29. Integration Levels
g
Process
Application
Data

30. Integration Techniques
g q
Integration
Techniques
Software
Data Based
Based
Database,
Standard Data Standard
Middleware
Element Enterprise
Data
Definition wide software
Warehouse
Multi-
Point To Point
Applications

31. Supporting Architectures
pp g
Layered Systems
Client / Server
Cli / S
N‐Tier

32. Software based Integration
Techniques
Techniq es
Driving Forces
• Easier access to enterprise wide data
• Reduced development time
• Reduced maintainence costs
Restraining Forces
• Mergers and Acquisitions
M d A i iti
• Depqrtements have differnt needs
• Dependence on software products
• Conversion to new software

33. Integration Techniques
g q
Integration
Techniques
Software
Data Based
Based
Database,
Standard Data Standard
Middleware
Element Enterprise
Data
Definition wide software
Warehouse
Multi-
Point To Point
Applications

34. Software Based Integration
Software Based Integration
Techniques
q
Middleware
Point – To – Point
P i t T P i t
Application Adapters
RPCs

35. Integration Techniques
g q
Integration
Techniques
Software
Data Based
Based
Database,
Standard Data Standard
Middleware
Element Enterprise
Data
Definition wide software
Warehouse
Multi-
Point To Point
Applications

36. Software Based Integration
Software Based Integration
Techniques
q
Multi – Applications
Message Bus
Message Broker

37. g
Driving Forces
• Consistent enterprise wide data
• Reduced development time
• Reduced maintenance costs
• Minimal effect on operational systems
Restraining Forces
g
• Costs of development
• Different semantics in data sources
• Semantic translation
• Lack of industry standard definitions
• Deciding what data to route
• Delays getting data updates distributed
• Data quality issues
• Brittleness of fixed record exchange

38. Integration Levels
g
Process
Application
Data

39. g
Driving Forces
• Consistent enterprise wide data
• Reduced development time
• Reduced maintenance costs
• Minimal effect on operational systems
Restraining Forces
g
• Costs of development
• Different semantics in data sources
• Semantic translation
• Lack of industry standard definitions
• Deciding what data to route
• Delays getting data updates distributed
• Data quality issues
• Brittleness of fixed record exchange

40. Service Oriented Architecture