The document discusses different approaches to integrating information from multiple systems, including: 1. Providing a uniform logical view of distributed data through approaches like mediated query systems, portals, federated database systems, and web services. 2. Realizing a common data storage through data warehouses and operational data stores that load and aggregate data from multiple sources. 3. Achieving integration through applications like workflow management systems that coordinate interactions between different systems and users.

1. Moving beyond ETL

2. Definition
In general, integration of multiple information
systems aims at combining selected systems so that
they form a unified new whole and give users the
illusion of interacting with one single information
system

3. Reasons for Integration
First, given a set of existing information
systems, an integrated view can be created to
facilitate information access and reuse through
a single information access point

4. Reasons for Integration
Second, given a certain information need, data
from different complementing information
systems is to be combined to gain a more
comprehensive basis to satisfy the need

5. Applications
In the area of Business Intelligence (BI) integrated information used
for querying and reporting for
• Statistical Analysis
• OLAP
• Data Mining
In order to enable
• Forecasting
• Decision Making
• Enterprise-wide Planning

6. Integration Problem
• Users will be provided with homogeneous logical view of
data physically distributed over heterogeneous data
sources
• All data has to be
represented using the same
abstraction principle
(unified global data model
and unified semantic)

7. Kinds of Heterogeneity
• Hardware and Operating Systems
• Data Management Software
• Data Models, Schemas and Semantic
• Middle-ware
• User Interfaces
• Business Rules
and Integrity Constraints

8. Abstraction Levels

9. 1. Manual Integration
• Users directly interact with all relevant
information systems and manually integrate
selected data
• Users have to deal with different user interfaces
and query languages
• Users need to have detailed knowledge on
location, logical data representation, and data
semantics.

10. 2. Common User Interface
• The user is supplied with a common user
interface (e.g. a web browser) that provides a
uniform look and feel
• Data from relevant information systems is still
separately presented
• Homogenization and integration of data yet has
to be done by the users
• For instance, as in Search Engines

11. 3. Integration by Applications
• Uses Integration applications that access various
data sources and return integrated results to the
user
• Practical for a small number of component systems
• Applications become increasingly fat as the
number of system interfaces and data formats to
homogenize and integrate grows

12. 4. Integration by Middle-ware
• Middleware provides functionality used to
solve aspects of the integration problem
• Integration efforts are still needed in
applications
• Different middleware tools usually have to be
combined to build integrated systems.

13. 5. Uniform Data Access
• A logical integration of data is accomplished at
the data access level
• Global applications are provided with a unified
global view of physically distributed data
• Global provision of physically integrated data can
be time-consuming
• Data access, homogenization, and integration
have to be done at runtime

14. 6. Common Data Storage
• Physical data integration is performed by
transferring data to a new data storage
• Local sources can either be retired or remain
operational
• In general, provides fast data access
• If local data sources are retired, applications
have to be migrated to the new data storage
• In case local data sources remain operational,
periodical refreshing of the common data
storage needs to be considered

15. Important Examples
• Mediated Query Systems
• Portals
• Data Warehouses
• Operational Data Stores
• Federated Database Systems (FDBMS)
• Workflow Management Systems (WFMS)
• Integration by Web Services
• Peer-to-Peer (P2P) Integration

16. Mediated Query Systems
• Represent a uniform data access solution by
providing a single point for read-only querying
access to various data sources
• Uses a mediator that contains a global query
processor to send sub-queries to local data
sources; returned local query results are then
combined

17. Portals
• Another form of uniform data access are
personalized doorways to the internet or
intranet
• Each user is provided with information tailored
to his information needs
• Web mining is applied to determine user-
profiles by click-stream analysis

18. Data Warehouses
• Realize a common data storage approach
• Data from several operational sources (OLTP)
are extracted, transformed, and loaded (ETL)
into a data warehouse
• Analysis, such as OLAP, can be performed on
cubes of integrated and aggregated data

19. Operational Data Stores
• A second example of a common data storage
• A “warehouse with fresh data” is built by
immediately propagating updates in local data
sources to the data store
• Up-to-Date integrated data is available for decision
support
• Unlike in data warehouses, data is neither cleansed
nor aggregated nor are data histories supported

20. Federated Database Systems
• Achieve a uniform data access solution by
logically integrating data from underlying
local DBMS
• Implement their own data model, support
global queries, global transactions, and
global access control

21. Workflow Management Systems
• Represent an integration-by-application approach
• Allow to implement business processes where
each single step is executed by a different
application or user
• Support modeling, execution, and maintenance of
processes that are comprised of interactions
between applications and human users

22. Integration by Web Services
• Performs integration through software components
(web services) that support machine-to-machine
interaction by XML-based messages conveyed by
internet protocols
• Depending on offered integration functionality either
represent
- a uniform data access approach, or
- a common data access for later manual or
application-based integration

23. Peer-to-Peer (P2P) Integration
• A decentralized approach to integration between
distributed peers where data can be mutually shared
and integrated
• Depending on offered integration functionality either
represent
- a uniform data access approach, or
- a common data access for later manual or
application-based integration

24. Semantic Data Integration