Best Practices for Optimizing Performance During Planning
There are actions you can take to optimize your system resources when using planning features in SAP Analytics Cloud.
System resources used in one feature area can sometimes impact the performance of other features using the same model. For example, if multiple users have large private versions on a model, this could impact performance of data actions and multi actions, data entry, or publishing versions.
If you do not have the required resources available, you may experience errors when using planning features and need to try again later. We recommend taking the following actions when possible to help improve performance during planning.
Version Management
When working with public and private versions, there are a few options to improve performance:
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Delete unused private versions and revert unused edits to public versions on your model.
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Note that large private versions created by other users may also impact performance. A user with Delete permission for the model can delete all private versions from the model preferences. For more information, see Planning.
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Filter the data that you copy to private versions.
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When creating a new private version, you can choose the data you want to copy to the new version. It is recommended to only copy relevant data if you are working with a large amount of data. For more information, see Creating Versions.
- If you have the recommended planning area enabled on the model, you can choose to only copy a subset of data based on data access control, data locking, or both. For more information about using the recommended planning area, see Optimize Planning Models Using the Planning Area.
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Limit the public version data you put into edit mode.
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If you have the recommended planning area enabled on the model, you can choose to only put the recommended planning area into edit mode. For more information, see Planning on Public Versions.
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- Define read data access control on the model. This ensures that non-admin planners will create private versions or edit public versions with a configured restricted data snapshot. For more information, see Set Up Data Access Control.
Data Actions, Multi Actions, and Allocations
Data actions, multi actions, or allocations running in the background may impact the performance of other planning activities. There are a few actions you can take to improve performance when working with these features.
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Filter the data you are running the data action, multi action, or allocation on.
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For more information on how to filter measures and members, see Add Steps to Your Data Actions, Automate a Workflow Using Multi Actions, and Build an Advanced Allocation Process.
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For data actions, avoid using calculated accounts or accounts with exception aggregation as source members if possible.
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For more information, see Copy Steps with Calculations and Exception Aggregation.
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For advanced formula steps, review this topic for tips on how to optimize your script's performance: Optimize Advanced Formulas for Better Performance
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For multi actions, if you will be adding multiple data actions based on the same model and version, it is recommended to embed these data actions into a new data action first. You can then add the new embedded data action to your multi action to improve performance.
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For more information on embedded data actions, see Adding an Embedded Data Action Step.
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- For allocations, breaking down an allocation by many reference members can impact performance. Try filtering the reference
dimensions instead.
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For more information, see Using Advanced Settings in Your Allocation Step.
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Data Entry
There are a few options to help you improve performance when working with data entry.
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When possible, avoid pasting data to many different members and dimensions in a table.
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When there are multiple dimensions in the table, you can paste to different sets of members for each dimension. To avoid slow performance, you'll be notified when you try to paste to an area that includes a large number of different sets. For more information, see Copying and Pasting Cell Values.
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For performance tips related to mass data entry, see Performance Considerations.
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- If your model contains many dimensions where the Unassigned member is not available, spreading data to all leaf members for each
dimension may result in slow performance.
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You'll either get a warning about slower performance, or a message to filter the data or change the target cell to create fewer data records in a single operation.
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Deleting values may also affect performance for queries and planning. For more information, see Performance Considerations.
Model Preferences
For details on how you can optimize performance using model preferences, see Set Up Model Preferences.