Xtensible has made a strategic decision to establish an end-to-end Enterprise Semantic and Metadata Management solution Affirma thereby discontinuing the support of CIM EA. Affirma supports the IEC Electric Utility Standard CIM (Common Information Model) through the IEC UCA Group and also supports other industry standard models such at the BIAN, tmforum SID, IEC CIM and others in conjunction with offering complete data-lifecycle management.
Affirma goes beyond CIM EA functionality
All the functionality available by CIM EA to support the IEC Electric Utility Standard CIM (Common Information Model) and CIM Profiles is provided by Affirma. This includes:
- Creating a CIM Profile
- Adding classes, attributes, and associations to a CIM Profile
- Edit an existing CIM Profile
- Adjust multiplicity, root element and abstract settings
- Create and organize CIM Profile Groups
- Generate artifacts
Affirma supports all previous CIM EA capabilities and in addition links the common information data model to other core business capabilities necessary for electric utilities:
|Enterprise Semantic Model
Manage your Enterprise Semantic Model across your data architecture. It is a harmonized superset of your data sources, with the ability to make use of industry standards such as the BIAN, tmforum SID, IEC CIM and others.
Ability to build, manage and update your data. The Data Catalog includes industry standard models, proprietary models, interfaces and other schemas.
Ability to build a common data definition across your organization by generating it from your semantic definitions. This includes the contextual information for your data sharable between business and IT.
Ability to generate schemas from your common data definition. Data Designs are platform independent schemas supporting DDL, XSD, JSON, etc.
Ability to describe the functionality of web-services and micro-services. Integration Design generates WSDL, SOAP, etc.
Ability to connect source systems or interfaces to profile data. Statistical analysis, with attribute assessments, correlation identification and cleanup suggestions are possible.
Ability to understand both upstream and downstream lineage tracing of your data capturing data origin, user action and more. It is foundational for utilization of graph-node capabilities and AI and ML integration.
|Mapping and Transformation
Ability to code, store and execute mappings and transformations and use for data verification purposes. Mappings and Transformations are reusable and therefore ensure consistency.