Reduce Complexity. Gain Business Value.
The importance of Reference Data
Reference data in Affirma is comprised of data models, data schemas, integration schemas, and other data definitions. Gathering these is the first step in being able to integrate them into your data architecture, for access across multiple technologies and platforms, regardless if your approach is based on a data fabric, a data mesh or a combination of both.
Consider all the different sources of reference data you have within your organization. Applications, databases, data warehouses, industry data models, API's, the number is endless.
Ask yourself if you are managing them effectively?
We have 100's of applications and databases, each one has its own data definition.
How do we manage them?
Information Technology Group
SOMETHING TO CONSIDER
3 steps to Reference Data
You might ask yourself how do I start using Affirma for managing reference data? The amount of reference data you have is no doubt massive. The key is to take a focused approach and expand over time. Consider starting with a specific business area or domain, or a different approach is to begin with a specific project or program implementation. Either way we suggest following as basic 3 step approach.
Define how to organize your Reference Data
Determine how you are going to organize your data. You could group by business capabilities, business area, business domain or data object domains. Our typical approach is to organize the data by business capabilities or business function. Affirma gives you the flexibility to adapt to what will best suit your organization.
Identify and import your Reference Data
Taking a focused approach you must identify and obtain your reference data sources. Within Affirma you will utilize the import wizard to import the reference data into the hierarchy you have created previously.
Use your Reference Data
You will make use of relevant parts of your reference data to build your enterprise semantic model, which will later enable you to design your integration and data stores, link to data mapping and data transformation.