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Convert a Dataflow to a Recipe

To use joins, aggregates, and sentiment detection in Data Prep, convert your dataflows to recipes. However, if your dataflow achieves your desired outcome, there’s no need to convert it, and you can continue using it. But consider using recipes for new Data Prep jobs because they offer more features.

Required Editions

Available in: Salesforce Classic and Lightning Experience
Available for an additional cost in: Enterprise, Performance, and Unlimited Editions
Permission Sets Needed
To convert a dataflow to a recipe:

Edit CRM Analytics Dataflows

OR

Edit Dataset Recipes

Before you convert a dataflow, keep these considerations in mind.

Warning
Warning The conversion tool doesn’t guarantee a fully automated conversion. After conversion, identify and address issues and validate the business logic.
  • Recipes don’t support some dataflow parameters or have implementation differences that require review or modification. See Dataflow Conversion Mapping.
  • Conversion creates one recipe per dataflow. You can convert a dataflow multiple times. Each conversion replaces the previous recipe. If you want to keep a converted recipe, save it as a new recipe to avoid overwriting it.
  • The original dataflow and its sync schedule are unchanged.
  • You don’t need a dataflow to create a recipe. See Create a Recipe with Data Prep.
  1. In Data Manager (Legacy), select Convert to Recipe from the dataflow’s dropdown menu.
    Shows Convert to Recipe option appears in dataflow dropdown.
    Conversion requires a valid dataflow with available input data sources. Only convert dataflows that have run successfully recently. Don’t convert an invalid dataflow.
  2. View the new recipe.
    Review and address any warnings and errors, as indicated by the The node warning icon, an orange triangle with an exclamation mark in the center. and The node error icon, a red circle with a diagonal red line through the center. icons against nodes and in the recipe editor header.
  3. Save and run the recipe.
  4. Compare the converted recipe’s output datasets, which have “_df2R3” appended to their names, to the dataflow’s datasets.
  5. Replace the dataflow with the recipe.
    1. To have your dashboards and references use the recipe’s datasets, change the recipe’s output dataset API names to match the dataflow’s dataset API names. Alternatively, update your dashboards and other references to use the recipe dataset names.
    2. Unschedule the dataflow and schedule the recipe.
    3. Consider deleting the dataflow’s datasets.
  • Dataflow Conversion Mapping
    During conversion, dataflow functionality is mapped to similar recipe functionality. Consider the mapping specifications when evaluating the conversion of your dataflows to recipes.