Enterprise Semantic Model

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The importance of an Enterprise Semantic Model

Semantic models are necessary when you want to understand and describe how things work and relate, and when you need to unambiguously exchange or reuse information. Today, new complex questions looking for answers have created a need to provide relevant data to stakeholders outside of your department and even outside of your business for widely connected datastores. Taking a semantic approach to managing your data will allow for teams to exploit connected data for new digital business insights.

The semantic model defines the meaning of the data and the shared relationships between datasets. It leverages a common format and understanding. This brings reusability and reduces future design time with the data.

Ask yourself if you have a common understanding of data?

"We lack a common definition of data across our systems and solutions, making project delivery time consuming"

Information Technology Group


Establishing an Enterprise Semantic Model is much more than an Information Technology group function. This requires the involvement of the business area domain. Determine early on the process by which IT and the business will work together.

Could you benefit from an Enterprise Semantic Model?


3 steps to Enterprise Semantic Modeling

You might ask yourself how do I start using Affirma to create an Enterprise Semantic Model for my organization? This may seem like a huge undertaking. Consider your organization strategic initiatives and focus where the key value of the data will be. We suggest you follow as basic 3 step approach.

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Determine the focused delivery approach

Ask yourself what the key initiatives are within the organization coming down the pipeline?  Are there major system upgrades or replacement?  Are there a set of analytic use cases for consideration?  Consider core data objects or business data domains that are involved.

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Select data from the Data Catalog for building your Enterprise Semantic Model

Select relevant data from the Data Dictionary library as building blocks for the Enterprise Semantic Model and initiate a gap analysis. This is where you start to harmonize data across your data architecture. This process involves collaboration between IT and respective business groups.

Identify design requirements and build with continous refinement

Based upon the design requirements, the data model objects and associations, you will add to your Enterprise Semantic Model the associated data elements. This may require extending the model to support additional requirements.  Establish common definitions working with the business area domain experts. The semantic model will continuously be refined and expanded project by project.

Affirma allows you to establish a common definition of data, for reusability, and delivery of data to support data-in-motion and data-at-rest.

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