Managing LDM Project Changes in CloudConnect

Your logical data model can be published into a GoodData project that already contains some LDM components. When the model is published to the platform, the LDM Modeler inspects the existing LDM and tries to merge the new LDM changes into it.

  • To show only the high-impact changes, select the High-impact changes checkbox and deselect the Low-impact changes checkbox.

  • By default, CloudConnect attempts to preserve the data on the platform. To review data management options, click the Advanced options.

    • To preserve the data in the project while the logical data model is being updated, click the Preserve data checkbox.
    • If it is OK to delete the existing data in the project, choose to overwrite the data model. Click the Overwrite checkbox.

Recommendations for Changing LDM Objects

  • In general, changes that are unlikely to cause problems include adding fields to a dataset.

  • Removing a field is almost always a high-impact change, since multiple metrics and reports may be using the removed item.

  • Changing the type of a field is a high-impact change that may cause data loss in the project.

General Tips:

  • When making changes to your logical data model, you should track the objects that have been modified from the previous version. Through the Manage page in the GoodData Portal, you can identify the other GoodData project objects that use these modified objects, which may be negatively impacted by these changes. For more information on this process, see Managing LDM Dependencies in CloudConnect.

  • When moving objects, do not delete from the source dataset and add again in the destination dataset. All references to the old object are lost. Instead, click and drag the object to the new dataset.

  • In general, make small changes to your data model and validate. See Validating Your Data Model in CloudConnect.

  • You can also test the effects of these changes. When you publish to the server, you are provided information on which changes are high-impact and are therefore likely to cause data loss. Back out of publishing these changes if you are unsure or uncomfortable with the effects. For more information, contact GoodData Customer Support.