Build a recipe in CRM Analytics Data Prep to combine and clean source data, then write it to a dataset that dashboards can use. Make sure the source objects are synced first so the recipe reads a current local copy.
- Open Data Prep and create a recipe
In CRM Analytics, go to Data Manager, open the Recipes (or Dataflows and Recipes) area, and click Create Recipe. A blank Data Prep canvas opens.
- Add input data
Add an Input node and pick your source, such as a synced Salesforce object, an existing dataset, or a connected external source. Add a second Input node if you plan to join or append another stream.
- Transform and combine
Add a Transform node for calculated columns, type conversions, and cleaning. Use a Join node to add related columns, a Filter node to drop unwanted rows, and an Aggregate node to roll up to a higher grain. Select any node to preview its results.
- Add an Output node
End the recipe with an Output node. Name the target dataset, choose the app it belongs to, and set a security predicate if you need row-level access control.
- Save, run, and schedule
Save the recipe, then run it to build the dataset. Schedule it to run on a recurring cadence so the dataset stays fresh, ideally after the related Data Sync job completes.
The synced object, dataset, or connected source the Input node reads. Sync source objects first so the recipe reads a current local copy.
The name of the dataset the Output node creates or overwrites. Dashboards and lenses query this dataset.
The CRM Analytics app that stores the output dataset and controls who can access it.
A row-level security rule on the output dataset that limits which rows each user can see.
- If the source object is not synced, the recipe still runs but reads slower and may miss recent records; pre-pull with Data Sync first.
- Running a recipe overwrites its target dataset, so a broken change replaces the good dataset everywhere downstream. Use version history to restore.
- Transformations run in the order placed inside a Transform node, so a derived column must come after the cleaning step it depends on.
- Scheduling a heavy recipe too frequently wastes run capacity; match the cadence to how fresh the analysis truly needs to be.