|
Business Benefits | Technical
Benefits
Business Benefits
Data semantics inspires a vision in which data carries unambiguous
business meaning that can be used accurately and flexibly without
prior knowledge of data’s specific format. Semantic Information
Management (SIM) addresses the core of the data problem by capturing
the precise meaning of data in agreed-upon terms. Key elements of
the architecture are:
- Knowing your data (metadata)
- Knowing your business (Information Model)
- Understanding your data (data semantics)
SIM creates value by delivering higher quality
business information, providing the flexibility to support business
change and making IT costs lower and more predictable. Its benefits
are felt in both specific targeted projects and enterprise-wide
initiatives.Improve Information Quality
Quality information frequently determines the success or failure
of both major and minor IT projects. Most CEOs have experienced
the adverse effects of decisions based on poor information, with
inaccurate quality data not being accessible in the format or
display required.
Increase Business Agility
Business agility is the ability of business to proactively respond
to the ever-changing business landscape while leveraging existing
IT investments. Agility requires an IT infrastructure that is
adaptive, with the capacity to respond rapidly and appropriately
to business objectives. Companies that can make effective use
of a changing environment are better able to compete and thrive
in any business climate, but especially in tough economic times.
The true goal of service-oriented management, therefore, is to
remove the bottleneck that IT has on businesses' ability to be
agile.
Lower IT Costs
The amount of effort and budget currently spent maintaining redundant
data sources and manually mapping data assets from one to another
continues to rise in most large corporations IT monies spent retaining
and updating systems which should be decommissions impact both
business and IT planning Enterprises that can apply their IT budgets
to growth instead of to holding old sources afloat will win over
their competition.
Technical Benefits
Data Semantics
-
Fine-grained semantic mapping of data schemas
to ontologies (rationalization)
-
Automatic suggestions based on type, foreign
keys, etc.
-
Conditional mapping accommodates mixed data
sources
-
API allows automatic mapping of large numbers
of complex schemas using external logic
Metadata
-
Out-of-the-box support for most common schema
types: RDBMS, XML, COBOL Copybook, Java API, IMS, and XMI
-
Data Source API allows support of any other
data formats
-
Automatic synchronization of external data
source schemas after change
-
Configurable structured descriptors for
capturing metadata, including hyperlink support
Data Management
-
Impact Analysis analyzes changes in the
ontology, Business Rules, mappings and external data sources
-
Data Discovery for comprehensive data source
identification per concept
-
Categorize content based on packages
-
Keyword Search with navigable search
-
Test instances for demonstrating and validating
the ontology model and business rules
Data Integration
-
Generating transformations in executable
SQL, XSLT, Java Bean
-
Generic Transformation Designer for guiding
other transformation coding
-
Automatic embedding of business rules in
transformations
- Automatically update after change in the model, schemas, and
rationalization
Architecture: Information Modeling
- Four-layered Information Model: Packages (Subject Areas), Classes
(Entities), Properties (Attributes), and Business Rules
- Fully integrated modeling environment
- Re-use of ERD & UML models from other modeling tools
- Reverse engineering of schemas and external logical models into
ontology
- Full support for ontological methodology
- Export of W3C RDF/S and OWL (Ontology Web Language) standards
|
