Definition
In Tableau CRM (Einstein Analytics), a data preparation step that transforms, cleans, and combines datasets before analysis, using a visual recipe editor to define filters, joins, formulas, and aggregations.
Real-World Example
At their company, a business analyst at Clearwater Inc. leverages Preparation Recipe to improve how the organization tracks relationships and interactions. By setting up Preparation Recipe properly, the team gains better visibility into their customer base, which leads to more informed decisions and stronger customer relationships across the board.
Why Preparation Recipe Matters
In Tableau CRM (Einstein Analytics, now CRM Analytics), a Preparation Recipe is a data preparation step that transforms, cleans, and combines datasets before analysis, using a visual recipe editor to define filters, joins, formulas, and aggregations. Recipes are how analysts shape raw data into the form needed for dashboards and analysis without writing code or maintaining complex ETL pipelines.
Recipes are part of the broader CRM Analytics workflow: connect data sources, build recipes to prepare data, generate datasets, then build dashboards and lenses on top. Mature CRM Analytics deployments invest in recipe design because recipe quality directly affects what analysis is possible. Good recipes produce clean, well-structured datasets that enable rich exploration; poor recipes produce data that requires constant workarounds in dashboards and lenses.
How Organizations Use Preparation Recipe
- •Apex Analytics — Built recipes to combine Salesforce CRM data with marketing platform exports, producing unified datasets for cross-channel analysis.
- •MarketPulse — Maintains a library of recipes for common data preparation patterns, with new dashboards leveraging existing recipes.
- •SilverLine Corp — Treats recipe design as a first-class analytics activity, with discipline around naming, documentation, and reuse.