# Recipe and dataflow transformation choices

*CRM Analytics and Einstein Discovery Consultant Study Guide · Data Layer · Last updated November 3, 2026 · https://www.certifyforce.com/study-guide/crm-analytics-and-einstein-discovery-consultant/data-layer/recipe-and-dataflow-transformation-choices*

Which recipe transformation or node meets a requirement (bucket, split, dates, formula across rows, types and attributes, joins, append, aggregate, built-in machine learning), the dataflow transformation that matches it, and why the recipe preview is only a sample.

- Certification: Salesforce CRM Analytics and Einstein Discovery Consultant
- Exam section: Data Layer
- Study guide: https://www.certifyforce.com/study-guide/crm-analytics-and-einstein-discovery-consultant

**Official exam objective:**

> Given business/user requirements, perform data transformations in dataflows/recipes.

## What the exam expects

- Pick the recipe transformation for a value-shaping need: Bucket, Split, Format Dates, Extract, Date and Time, type conversion, Edit Attributes, Drop Columns.
- Build calculated columns with Formula, within one row or across rows with partition and order.
- Combine inputs with the right join type, Append or Aggregate, and work round the join key-pair limit.
- Choose the built-in machine learning transformation (Detect Sentiment, Cluster, Predict Missing Values, Time Series Forecasting, Discovery Predict).
- Map a requirement to the dataflow transformation (computeExpression, computeRelative, sliceDataset, augment, Delta) when a dataflow must stay.

Key terms: **Transform node** (the recipe node that holds a sequence of transformations); **multiple-row formula** (a Formula with window functions, Partition By and Order By); **lookup** (a join that keeps one output row per left row); **Append** (stacks rows of inputs that share columns); **preview sample** (the subset of rows the recipe editor shows while you build).

## Key facts

| Fact | Detail | Source |
|---|---|---|
| Recipe-only | Aggregate, Cluster, Detect Sentiment, Predict Missing Values, Split, Time Series Forecasting and more | [Why Use Recipes](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_prepare.htm&type=5&language=en_US) |
| Dataflow-only | Delta | [Why Use Recipes](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_prepare.htm&type=5&language=en_US) |
| Dataflow names | computeExpression (same row), computeRelative (across rows), sliceDataset (drop), augment (lookup) | [Why Use Recipes](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_prepare.htm&type=5&language=en_US) |
| Split | Two values per Split at a delimiter | [Transformations for Data Prep](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_recipe_transformations_overview.htm&language=en_US&type=5) |
| Formula across rows | Multiple row formula with Partition By and Order By | [Formula Transformation](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_recipe_transformation_formula.htm&type=5&language=en_US) |
| Edit Attributes | Labels, API names, precision, scale, text length, date formats | [Transformations for Data Prep](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_recipe_transformations_overview.htm&language=en_US&type=5) |
| Join keys | Up to 5 key pairs | [Prepare Your Data](https://trailhead.salesforce.com/content/learn/modules/wave_enable_data_integration_basics/wave_prepare_your_data) |
| Lookup vs join | Lookup keeps one row per left row; joins keep all matches | [Join Operations](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_recipe_join_operations.htm&type=5&language=en_US) |
| Aggregate pivot | Up to two dimension columns as columns | [Aggregate Node](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_recipe_aggregate_rows.htm&type=5&language=en_US) |
| Preview | A sample of the input, sized differently on the two pages; the run processes every row | [Preview Results](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_recipe_preview_results.htm&type=5&language=en_US), [Set Up the Preview](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_data_prep_create_recipe_set_preview.htm&type=5&language=en_US) |

## Check yourself

- Why can a left join change a dataset's grain when a lookup on the same key does not?
- When does a cross join make sense, given that it takes no keys?
- What length does a text calculated column get if you set none?
- Why might a node after a join show no sample rows while the full run returns data?

## Sources

- [Transformations for Data Prep Recipes](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_recipe_transformations_overview.htm&language=en_US&type=5)
- [Why Should I Use Recipes Instead of Dataflows?](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_prepare.htm&type=5&language=en_US)
- [Formula Transformation: Create a Calculated Column Based on an Expression](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_recipe_transformation_formula.htm&type=5&language=en_US)
- [computeRelative Transformation](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_computerelative_transformation.htm&type=5&language=en_US)
- [Join Operations](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_recipe_join_operations.htm&type=5&language=en_US)
- [Aggregate Node: Roll Up Data to a Higher Level](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_recipe_aggregate_rows.htm&type=5&language=en_US)
- [Prepare Your Data (Trailhead)](https://trailhead.salesforce.com/content/learn/modules/wave_enable_data_integration_basics/wave_prepare_your_data)
- [Preview Results in a Data Prep Recipe](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_recipe_preview_results.htm&type=5&language=en_US)
- [Set Up the Preview in a Recipe](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_data_prep_create_recipe_set_preview.htm&type=5&language=en_US)
- [CRM Analytics and Einstein Discovery Consultant Exam Guide](https://help.salesforce.com/s/articleView?id=005298935&language=en_US&type=1)

## About the full unit

The "Core concepts", "Exam traps" and "Worked scenario" sections of this unit, its 17 linked practice questions, and unlimited timed mock exams are included with the CRM Analytics and Einstein Discovery Consultant pack (USD $19): https://www.certifyforce.com/practice-exams