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Data Integration by Mind Map: Data Integration
5.0 stars - 1 reviews range from 0 to 5

Data Integration

Enterprise Integration (EI)

capability to integrate information and functionalities from a variety of information systems in an enterprise

Enterprise Information Integration (EII)

integration on data and information level, structural integration, semantic integration

principal approaches (database-centric), manual integration, common user interface, integration by applications, workflow management system (WFMS), business processes where each single step is executed by a different application or user, modeling, execution, and maintenance of processes that are comprised of interactions between applications and human users, integration by middleware, uniform data access, mediated query systems, provides single point for read-only querying access, sends subqueries to data sources, combines returned query results, portals, personalized doorway to the internet / intranet, federated database system (FDBMS), supports global queries / transactions / access control, fully-fledged DBMS (implement their own data model), integration-by-webservices, integration through software components that support machine-to-machine interaction over a network by XML-based messages that are conveyed by internet protocols, peer-to-peer integration, decentralized integration between distributed, autonomous peers, every data source needs to only provide semantic mappings to a set of neighbors it selects, and more complex integrations emerge as the system follows semantic paths in the network., with a P2P architecture there is never a single global mediated schema, since data sharing occurs in local neighborhoods of the network, common data storage, date warehouse (DWH), OLTP (online transaction processing) operational source systems, data is extracted, transformed and loaded (ETL) into a warehouse, OLAP (online analytical processing) can be performed on integrated and aggregated data, operational data stores, warehouse with "fresh" data, updates in data sources are propagated to data store, no data cleansing / aggregation / historisation

Enterprise Application Integration (EAI)

integration on the level of application logic

reasons / goal

single information access point

data consolidation turns diverse data into a more comprehensive basis

benefitary applications

Business Intelligence (BI)

querying / reporting on business activities

statistical analysis

Online Analytical Processing (OLAP)

data mining, forecasting, dicision making, enterprise-wide planning, gain sustainable competitive advantages

Customer Relationship Management (CRM)

integrated information on individual customers

business environemnt trends

current sales

Enterprise Information Portals (EIP)

integrated company information as personalized web sites

single access points for employees / customers / partners / public

e-Commerce / e-Business

enables and facilitates business transactions over computer networks

kinds of heterogenity

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hardware and operating systems

data management software

data models / schemas / semantics

middleware

user interfaces

business rules and integrity constraints

dependencies

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architectural view of integrated information system

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content / functionality of source systems

kind of information that is managed by source systems

alphanumerical

multimedial

structured

semi-structured

unstructured

requirements concerning autonomy of source systems

intended use of integrated information system

read-only

read/write access

performance requirements

available resources

time

money

human resources

know-how