Today, data management and engineering, along with the data models that these activities often generate are not as commonly maintained as has been the case historically. These data models were often used to forward engineer data engineer databases as part of a formal data management database design process. With the advent of big data, data lakes and self service BI, where the emphasis is on flexibility and rapid reporting development and turnaround, the venerable data management based models are not seen as so useful, and are instead seen to be "getting in the way" of the faster paced world of today.
Nevertheless, these data models are often seen to have a wealth of data documentation. Many organizations eye these models, not for their forward engineering value, but instead to be leveraged for table and column definitions, domains, validation rules, enumerations, etc. While it is often true that these models will have good and even well curated definitions and other such information, it is also true that data models were never really ideal when it comes to building reusable terminology, standardized definitions, etc. Instead, a definition for a given column will be repeated (reentered and not reused or shared) for each table in which that column appears.
Thus, it is generally not a good idea to simply import data models and use those for standard definitions and business names. Instead, it behooves the organization to migrate (and standardize/normalize) the wealth of information that these models contain into more future proof and flexible solutions such as a glossary, which retain what is uniquely valuable from these models, such as ER Diagrams.
Importing Data Models
First, we will import the data models. Oftentimes, one may point to the model repository for the respective tool, e.g., the Erwin Mart or ER/Studio Team Server. This way, one will have all the models conveniently imported as one repository model, and thus one may search multiple occurrences of the same data element (like a column that is repeated many times).
Steps
Import the models using the matching tool bridge as detailed in the Create a Model and Import Metadata section.
Example
For the demo, we will import from files. We will import four Erwin DM models:
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Accounts Payable
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Accounts Receivable
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Staging Data Warehouse
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Dimensional Data Warehouse.
Sign in as Administrator, go to MANAGE > Configuration and click the plus sign to Create a new Imported Model. Name it "Accounts Payable" and specify the erwin 9.x to 12.x Data Modeler (File) bridge.
For the File bridge parameter, browse to
C:\User\MITI-Admin\Demo\Models\MetadataManagement\Finance\CaErwin9Xml\AccountsPayable-LogicalPhysical.xml
SAVE and IMPORT.
Click OPEN.
