Mapping and Transformation
Reduce Complexity. Gain Business Value.
The importance of Data Mapping and Transformations
Data Mappings define the transformation of data between two data integration interfaces. This includes both object and attribute mapping from source to target, as well as any transformation the data content needs to undergo in the process.
Keeping track of multiple integration definitions across multiple systems in the organization as well as integrations to external systems is an impossible task if these integration designs are documented in individual documents, in differing formats and distributed through the enterprise.
Ask yourself how you keep track of multiple definitions across multiple systems?
"How can we manage our 4000+ integration mapping spreadsheets all in one controlled environment?"
Information Technology Group
SOMETHING TO CONSIDER
3 steps to Data Mapping and Transformation
You might ask yourself how do I start using Affirma for Data Mapping and Transformation and get out of the current process. Here is the approach we recommend building on previous steps:
Import existing data mappings or create new ones
Affirma allows you to leverage your existing mapping designs by transferring them to an Excel template and importing them into Affirma’s Data Mapping library. Alternatively, you can create a new mapping design, add your source and target schemas to it, and use Affirma’s graphical design interface to define your mapping design down to attribute level.
Publish your Data Mappings
Data mapping definitions can be exported or made available through the Affirma platform for review or approval. Once approved the designs can be made accessible through similar mechanisms to your system integration build team.
Maintain your Data Mappings
Remember to update the mappings with any changes agreed to during the integration build. Similarly, if updates to the data mapping design is required in future, make those changes in Affirma and publish as needed.