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Plan Your Migration from Model Administration Tool to Semantic Modeler

Plan Your Migration from Model Administration Tool to Semantic Modeler

Oracle Analytics has a seasoned, rich Semantic Model, which has been used by thousands of analytics customers over the past decades.

Today, I'm excited to share with you the next generation of Semantic modeller powered by Oracle Analytics.

Semantic Modeler is the next generation web-based tool for creating governed data models with rich business semantics, providing a simple and unified business view of data offering followings :

  • Modern browser-based data Modeling tool integrated into Oracle Analytics Cloud.

  • Rich governed data Modeling capabilities including physical, logical and lineage diagrams.

  • Tight integration with any Git-based platform in the public cloud.

  • Transparent Semantic Model Markup Language (SMML) generation to define semantic models.

  • An SMML editor with smart integration with an expression editor to validate calculations and advanced expressions.

  • Streamlined search integration that seamlessly shows the relationships among objects.

Steps required to migrate your semantic model from Model Administration Tool to Semantic Modeler.

Step 1 - Check the model's data source: Confirm that the model you want to migrate uses a data source that Semantic Modeler supports. Semantic Modeler only supports relational data sources. Be sure to remove or replace any unsupported data sources in the semantic model before migration.

Step 2 - Go to your Oracle Analytics development or test environment: Perform the semantic model migration in a non-production environment, such as an existing development or test environment, before making changes to your production environment.

Step 3 - Back up your environment: Use the Console to take a full snapshot of your development or test environment. You can use the snapshot to restore the environment if you discover issues after deploying the imported model.

Step 4 - Understand the differences between Model Administration Tool and Semantic Modeler : Understanding the functionality and features differences between Model Administration Tool and Semantic Modeler is must to ensure there are no gaps and you are fully prepared to migrate.

Step 5 - Prepare the semantic model in Model Administration Tool : Check and update the semantic model to ensure successful migration such as data source, logical dimensions, logical foreign keys, Primary keys and consistency check.

Step 6 - Import the model: Use the Semantic Modeler Create option to migrate the model. When you create the model, you have the option of importing the .rpd file into the new model, or importing the model deployed from Model Administration Tool

Step 7 - Modify the imported model and check consistency : Use Semantic Modeler to modify the migrated model and run the advanced consistency check.

Step 8 - Deploy the model : If the model is working as expected and passes the advanced consistency check, then deploy the model from Semantic Modeler.

Step 9 - Revert to Model Administration Tool if necessary : If you deployed the model from Semantic Modeler and discover issues such as visualizations not displaying the correct data, then use the Console to restore your environment to the state when the snapshot was taken.

Discover a seamless migration path from Model Administration Tool to Semantic Modeler with ease and Unlock a wealth of new data analytics experiences by following these steps.

With our expertise and skills, we ensure a convenient and secure migration process, leaving no room for gaps. Let's elevate your data analytics journey together!" Please reach out to us on and get access to a free demonstration of our solution.

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