Best Practices: Avoid the "Maximum Daily Analytics Dataflow Executions has been exceeded" error in CRM Analytics

The following best practices help you stay within the Maximum Daily Analytics Dataflow Executions limit by reducing unnecessary runs, consolidating dataflows, and optimizing run times. Apply these strategies proactively to avoid this error.

Optimize Dataflows and Recipes to run under 2 minutes

Dataflow and recipe runs under 2 minutes are excluded from this limit.

Determine your data freshness requirements

• First, consider how often your users actually need to see updated data for each dataset.
• Once you identify how often your datasets need to be updated, schedule their associated dataflows to run only when needed.
• The same guidance applies to recipes. Only schedule the recipe to run as often as users actually need to see fresh data.

Consider having your hourly dataflows start and stop running at specific times

• For dataflows scheduled to run hourly, you can specify a time of day for them to start and stop queueing. For example, users might not need updated data after business hours.
• The start time determines when the dataflow first runs each day; the stop time determines when the last dataflow run begins.
• For more information, see Schedule a Dataflow to Run Automatically.

Identify dataflows with common scheduling requirements and consider combining them

• If you have multiple dataflows using a similar schedule, consider combining them into a single dataflow and setting a schedule that meets the data freshness requirements for all included datasets.

Consider moving data manipulation tasks from recipes to dataflow nodes

• If you have multiple scheduled recipes performing data manipulation tasks on your datasets, these could quickly use a significant portion of your daily dataflow runs.
• There may be situations where you can move data manipulation tasks from a recipe to transformations such as computeExpression, append, or augment directly in the dataflow.
• For more information, see Transformations for Analytics Dataflows.