Integration

H. A. El‐GhareebI f i  S  DInformation Systems Dept.Faculty of Computers and Information SystemsMansoura UniversityMansoura Universityhelghareeb@mans.edu.eg

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

What is Integration?gEnterprises consume more than one application.E h  li i     f  i     k   i h   Each application can perform its own tasks with no need for others (Vice Versa: Interoperability).Vice Versa: Interoperability).Th  d ’      d     d   k   h  That doesn’t mean apps do not need to know others exist (Vice Versa: IntegrationVice Versa: Integration).E lExample:

Updating Customer Billing address in finance system i   d i  h /hi  billi   dd  i  CRMrequires updating her/his billing address in CRM.

Integration LevelsgProcess

Application

DData

Integration Techniquesg qIntegration TechniquesTechniques

Data Based Software Based

Standard Data Element

Definition

Database, Data

Warehouse

Standard Enterprise

wide softwareMiddleware

Point To Point Multi-ApplicationsApplications

Software ArchitectureThe sumsum of the nontrivial modulesnontrivial modules, processesprocesses, and datadata of the system  their structurestructure and exact datadata of the system, their structurestructure and exact relationshipsrelationships to each other, how they can be and are expected to be extendedextended and modifiedmodified  and on which expected to be extendedextended and modifiedmodified, and on which technologiestechnologies 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.

Common Software ArchitectureCommon Software Architecture Patterns

Data Flow

• Model‐View‐Controller 

Control Flow

• Call And Return a.k.a. Main program And • Presentation‐Abstraction‐Control• Pipe‐And‐Filter • Layered Systems• Microkernel

Subroutines• Implicit Invocation a.k.a. Event Based• Manager Model• Emulated Parallel

• 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

Integration LevelsgProcess

Application

DData

Integration Techniquesg qIntegration TechniquesTechniques

Data Based Software Based

Standard Data Element

Definition

Database, Data

Warehouse

Standard Enterprise

wide softwareMiddleware

Point To Point Multi-ApplicationsApplications

Pipe And Filter Architecturep

Pump Pipe Filter Pipe Filter Pipe Sinkp

Data Based Integration Techniquesg qStandard 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

Integration Techniquesg qIntegration TechniquesTechniques

Data Based Software Based

Standard Data Element

Definition

Database, Data

Warehouse

Standard Enterprise

wide softwareMiddleware

Point To Point Multi-ApplicationsApplications

Repository Software Architecturep y

Repository

Knowledge  Knowledge  Knowledge Knowledge Source

Knowledge Source

Knowledge Source

b i h iDatabase Integration TechniquesDatabasesDatabasesData warehouse

Driving Forces• Easier access to enterprise wide data• Reduced development time

R d d i t t• Reduced maintenance costs• Minimal effect on operational system• use of business intelligence software

Restraining Forces• Costs of development

iff i i d• Different semantics in data sources• Semantic translation• Lack of industry standard definitions• Deciding what data to warehouse• Delays in getting data to the warehousey g g• Redundancy of data• Data quality issues• Brittleness of fixed record exchanges• Performance Tuning

Integration LevelsgProcess

Application

DData

Integration Techniquesg qIntegration TechniquesTechniques

Data Based Software Based

Standard Data Element

Definition

Database, Data

Warehouse

Standard Enterprise

wide softwareMiddleware

Point To Point Multi-ApplicationsApplications

Supporting Architecturespp gLayered SystemsCli  / SClient / ServerN‐Tier

Software based Integration Techniq esTechniques

Driving Forces• Easier access to enterprise wide data• Reduced development time• Reduced maintainence costs

Restraining ForcesM   d A i iti• Mergers and Acquisitions

• Depqrtements have differnt needs• Dependence on software products• Conversion to new software

Integration Techniquesg qIntegration TechniquesTechniques

Data Based Software Based

Standard Data Element

Definition

Database, Data

Warehouse

Standard Enterprise

wide softwareMiddleware

Point To Point Multi-ApplicationsApplications

Software Based IntegrationSoftware Based Integration Techniquesq

MiddlewareP i t  T   P i tPoint – To – Point

Application AdaptersRPCsRPCs

Integration Techniquesg qIntegration TechniquesTechniques

Data Based Software Based

Standard Data Element

Definition

Database, Data

Warehouse

Standard Enterprise

wide softwareMiddleware

Point To Point Multi-ApplicationsApplications

Software Based IntegrationSoftware Based Integration Techniquesq

Multi – ApplicationsMessage BusMessage BusMessage Broker

Driving Forcesg• Consistent enterprise wide data• Reduced development time• Reduced maintenance costsReduced maintenance costs• Minimal effect on operational systems

Restraining Forcesg• Costs of development• Different semantics in data sources• Semantic translationSemantic translation• Lack of industry standard definitions• Deciding what data to route• Delays getting data updates distributedDelays getting data updates distributed• Data quality issues• Brittleness of fixed record exchange

Integration LevelsgProcess

Application

DData

Driving Forcesg• Consistent enterprise wide data• Reduced development time• Reduced maintenance costsReduced maintenance costs• Minimal effect on operational systems

Restraining Forcesg• Costs of development• Different semantics in data sources• Semantic translationSemantic translation• Lack of industry standard definitions• Deciding what data to route• Delays getting data updates distributedDelays getting data updates distributed• Data quality issues• Brittleness of fixed record exchange

Service Oriented Architecture