Create a schema mapping (manually defined columns)

This procedure describes the process of creating a schema mapping using the Build custom schema option on the AWS Entity Resolution console. Use this creation method to manually define the input fields using a guided flow.

To create schema mapping using manually defined columns

1. Sign in to the AWS Management Console and open the AWS Entity Resolution console with your AWS account, if you haven't yet done so.

2. In the left navigation pane, under Data preparation, choose Schema mappings.

3. On the Schema mappings page, in the upper right corner, choose Create schema mapping.

4. For Step 1: Specify schema details, do the following:

   1. For name and creation method, enter a Schema mapping name and an optional Description.

   2. For Creation method, choose Build custom schema.

   3. For Unique ID, enter a unique ID to identify each row of your data.

      For example: Primary_key, Row_ID, or Record_ID.

      Note

      The Unique ID column is required. The Unique ID must be a unique identifier within a single table. However, across different tables, the Unique ID can have duplicate values. If the Unique ID isn't specified, isn't unique within the same source, or overlaps in terms of attribute names across sources, then AWS Entity Resolution rejects the record when the matching workflow is run.

   4. (Optional) If you want to enable Tags for the resource, choose Add new tag, and then enter the Key and Value pair.

   5. Choose Next.

5. For Step 2: Map input fields, do the following:

   1. For Input fields for matching, add the Input field, Input type, and Match key.

      You can add up to 25 input fields.

      The Input type helps you classify the data. The Match key enables input field comparison to your matching workflow.

      Note

      If you're creating a schema mapping to use with the LiveRamp provider service-based matching technique, then you can specify the Input type as LiveRamp ID. If you want to include PII data in the output, then you must specify the Input type as Custom string.

   2. (Optional) For Input fields for pass through, add the input fields that won't be matched.

   3. Choose Next.

6. For Step 3: Group data:

   1. Choose the related Name fields, and then enter the Group name and Match key.

      For example, choose input fields First name, Middle name, and Last name, and then enter a Group name called “Full name” and a Match key called “Full name” to enable the comparison.

   2. Choose the related Address fields, and then enter the Group name and Match key.

      For example, choose input fields Home street address 1, Home street address 2, and Home city, and then enter a Group name called “Shipping address” and a Match key called “Shipping address” to enable the comparison.

   3. Choose the related Phone number fields, and then enter the Group name and Match key.

      For example, choose input fields Home phone 1, Home phone 2, and Cell phone, and then enter a Group name called “Shipping phone number” and a Match key called “Shipping phone number” to enable the comparison.

      If you have more than one type of data, you can add more groups.

   4. Choose Next.

7. For Step 4: Review and create, do the following:

   1. Review the selections that you made for the previous steps and edit if necessary.

   2. Choose Create schema mapping.

      Note

      You can’t modify a schema mapping after you associate it with a workflow. You can clone a schema mapping if you want to use an existing configuration to create a new schema mapping.

After you create the schema mapping, you're ready to create a matching workflow or create an ID namespace.