---
schema_version: "1"
id: 618867b43e455f7425c424caaa2c6033f38989b6b38911d830dc5ea2bb1398a2
title: augment Transformation
collection: admin
version: current
locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/analytics/264-0-0/bi_integrate_augment_transformation.md
canonical_url: https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_augment_transformation.htm&release=264.0.0&type=5
source_site: help.salesforce.com
content_type: documentation
content_hash: 3aa23b565d7133e1edcf8f96a24cabfe26b3defaf6248c0541367314ba3d5e8c
description: The augment transformation adds columns to a dataset from another related dataset. The resulting, augmented dataset enables queries across both related input dataset. For example, you can augment the Account dataset with the User dataset to enable a query to return account records and the full names of the account owners.
products:
  - CRM Analytics
  - Cross Cloud
release: "264"
---
# augment Transformation

The augment transformation adds columns to a dataset from another related dataset. The resulting, augmented dataset enables queries across both related input dataset. For example, you can augment the Account dataset with the User dataset to enable a query to return account records and the full names of the account owners.

![Note](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-analytics-bi-264-0-0-production-enus/ec791473-f5b4-4f64-a656-9104f455d966/images/icon_note.png)

Note To add columns from a related object in a Data Prep recipe, see [Join Node: Add Related Columns of Data to the Recipe](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_recipe_join_data.htm&release=264.0.0&type=5 "Use a join node in CRM Analytics to add columns of data from related objects to existing data in a recipe. When working with CRM Analytics datasets and external objects, add a join node on the recipe canvas. When working with Salesforce objects, you can either create a join on the recipe canvas or join the data when you first create your dataset on the Add Input Data screen."). To do it in a Data Prep Classic recipe, see [Add More Data in a Recipe](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_data_prep_recipe_add_data.htm&release=264.0.0&type=5 "You can add columns of data from related objects to existing data in a recipe. Depending on how you want to combine the new data, use one of the following methods: lookup, left join, right join, inner join, or full outer join.").

When you create the transformation, you identify each input dataset as the left or right dataset and specify the relationship between them. CRM Analytics combines all the columns of the left dataset with only the specified columns from the right dataset. (Keep in mind that each dataset can’t have more than 5,000 (including up to 1,000 date fields) columns.) CRM Analytics adds the relationship to column names from the right dataset, which is useful when the left and right dataset have columns with the same names.

For each record in the left dataset, the augment Transformation transformation performs a lookup to find a matching record in the right dataset. To match related records, the augment Transformation transformation uses a match condition. You specify the match condition based on a key from each dataset. A key must be a dimension. A key can be a single-column key or a composite key. For a match condition based on a composite key, the keys for both dataset must have the same number of columns, specified in the same order.

![Tip](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-analytics-bi-264-0-0-production-enus/ec791473-f5b4-4f64-a656-9104f455d966/images/icon_tip.png)

Tip To augment three or more dataset, augment two dataset at a time. For example, to augment three dataset, augment the first two dataset, and then augment the resulting dataset with the third dataset.

![Example](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-analytics-bi-264-0-0-production-enus/ec791473-f5b4-4f64-a656-9104f455d966/images/icon_example.png)

Example

Let’s look at an example of the augment Transformation transformation. In this example, you want to extract data from the Opportunity and Accounts objects, and then match the data based on the account ID field.

![The Opportunity and Account EdgeMarts are related based on Opportunity.Account ID and Account.ID columns.](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-analytics-bi-264-0-0-production-enus/ec791473-f5b4-4f64-a656-9104f455d966/bi/images/bi/bi_integrate_augment_inputs.png)

 
| Dataflow | Augment Node in Dataflow |
| --- | --- |
| ![Example dataflow in dataflow editor with augment node highlighted](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-analytics-bi-264-0-0-production-enus/ec791473-f5b4-4f64-a656-9104f455d966/bi/images/bi/bi_integrate_dataflow_editor_augment_example.png) | ![Augment node dialog in dataflow editor](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-analytics-bi-264-0-0-production-enus/ec791473-f5b4-4f64-a656-9104f455d966/bi/images/bi/bi_integrate_dataflow_editor_augment_node.png) |

Here’s the dataflow JSON.

```
{
  "sfdcDigest_Account": {
    "action": "sfdcDigest",
    "parameters": {
      "fields": [
        {"name": "Id"},
        {"name": "Name"}
      ],
      "object": "Account"
    }
  },
  "sfdcDigest_Opportunity": {
    "action": "sfdcDigest",
    "parameters": {
      "fields": [
        {"name": "Id"},
        {"name": "Name"},
        {"name": "Amount"},
        {"name": "StageName"},
        {”name": "CloseDate"},
        {"name": "AccountId"},
        {"name": "OwnerId"}
      ],
      "object": "Opportunity"
    }
  },
  "augment_Oppt_Acct": {
    "action": "augment",
    "parameters": {
      "operation": "LookupSingleValue",
      "left": "sfdcDigest_Opportunity",
      "left_key": [
        "AccountId"
      ],
      "relationship": "OpptyAcct",
      "right": "sfdcDigest_Account",
      "right_key": [
        "Id"
      ],
      "right_select": [
        "Name"
      ]
    }
  },
  "Create OpptsAccts": {
    "action": "sfdcRegister",
    "parameters": {
      "alias": "Opportunity_Account",
      "source": "augment_Oppt_Acct",
      "name": "Opportunity_Account"
    }
  }
}
```

After you run the dataflow, CRM Analytics creates and registers the Opportunity\_Account dataset. It also adds the relationship as a prefix to all columns from the right dataset.

![The Opportunity-Account EdgeMart contains the following columns: ID, Opportunity Name, Amount, Stage, Closed Date, Account ID, Acct\_Account Name, Acct\_Annual Revenue, and Acct\_Billing Address.](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-analytics-bi-264-0-0-production-enus/ec791473-f5b4-4f64-a656-9104f455d966/bi/images/bi/bi_integrate_opportunity-account_dataset.png)

- **[Special Cases for Matching Records with the augment Transformation](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_augment_match_operations.htm&release=264.0.0&type=5)**  
    For each record in the left dataset, the augment transformation performs a lookup to find a matching record in the right dataset. However, it’s critical that you understand how the augment transformation handles special cases when matching records.
- **[augment Parameters](https://help.salesforce.com/s/articleView?id=analytics.bi_integrate_augment_operation.htm&release=264.0.0&type=5)**  
    When you define an augment transformation, you set the action attribute to `augment` and specify the parameters.