Reduce Complexity. Gain Business Value.
The importance of Data Dictionary
The purpose of a Data Dictionary is to provide names, definitions, and attributes for the data that is being used within your technology landscape. Stakeholders need to be able to quickly find the correct data they need for their specific purposes, whether the data is used in new ways for business innovation or for solving business problems.
Correct use of data allows for mitigation of project delivery risks and provides confidence within the delivered solutions.
How do you integrate what is defined to what is actually designed and implemented?
"How do we connect our Data Dictionary to what is being designed and built?"
SOMETHING TO CONSIDER
3 steps to Data Dictionary
You many have a solution or tool that you using to manual document a Data Dictionary. Does it fully integrate into the data designs and implementation process? Perhaps you don't have a means today for documenting a Data Dictionary. Where do you start? Affirma can support you in both instance with just a few steps.
Identify existing Data Dictionary and integrate
Gather the existing solutions or tools in which you have data definitions available.
Harmonize your Data Dictionary across the Enterprise Semantic Model
The Enterprise Semantic Model is what is utilized to create the data designs and feeds the data dictionary. If you integrated with an existing data definition solution or tool you need to harmonize them with the Enterprise Semantic Model. This will ensure that data designs are built off of a common definition. If you started your Data Dictionary journey with Affirma the Data Dictionary will be generated based upon the Enterprise Semantic Model.
Continuous development and refinement
As changes to the technology landscape occurs you will continue to update designs based on the Enterprise Semantic Model which will harmonize your Data Dictionary and provides an easy way to ensure that there is clarity around data for both IT design and implementation with the Business.