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            Prepare Your Data for a Clean Room

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            Prepare Your Data for a Clean Room

            To share segments in a clean room, complete these steps to prepare your data. Preparation includes required steps such as ingesting the data, mapping the DLO to a DMO, hashing fields to protect personal information, and creating segments. You can share segments only in a clean room.

            Required Editions

            Available in: All Editions supported by Data Cloud. See Data Cloud edition availability.
            Note
            Note If you already created Salesforce segments with a unique segment name and match key, you can directly create a DMO containing all the fields you want to use as match keys and hash sensitive fields for clean rooms.

            This process is a multi-step solution that can require different roles and permission sets to complete in Data Cloud. Bookmark this page or keep it open in a separate window to refer to this topic.

            See Also

            Connect Data to Data 360

            You can ingest profile data and engagement data. To ingest both types, create a separate data stream for each type. Your profile data must contain a unique ID for the individual, such as an email address, phone number, PPID, or device ID. Your data must also be hashed with the SHA256 algorithm so that it’s in lowercase characters with no spaces. If your data isn’t hashed with the SHA256 algorithm, you can transform it after ingestion.

            Required Editions

            User Permissions Needed
            To connect data to Data Cloud Data Cloud Architect permission set
            Choose your data ingestion method based on your data source.
            • Use accelerated query federation to connect your external data sources with Data 360 and access your data without moving it. Clean rooms support accelerated data streams only. File federation and live-query data federation are not supported.
            • Create a data stream by uploading a CSV file or by using a data kit.
            • Use a file-based storage connector, such as Amazon S3 or Google Cloud Storage.
            • Use a Salesforce CRM connector to ingest data from a connected Salesforce org.
            • Capture real-time data from a website or mobile app by using the Web and Mobile App connector.

            Map Data to Data Model Objects

            Associate the ingested data stream or DLO to the relevant standard DMOs in Data Cloud.

            Required Editions

            User Permissions Needed
            To map data for a clean room Data Cloud Architect permission set
            1. On the Data Streams tab, open the data stream that you created for the clean room.
            2. In the Data Mapping section, click Start.
            3. Click Select Objects and select the target DMOs.

              You can map profile data to the Individual - latest DMO or Contact Point DMO. For engagement data, use an appropriate standard DMO, but map the contact point to the individual - latest DMO. If you’re a provider, you can also create a custom DMO to map your data.

            4. If you’re a provider and want to add a custom object, in the Custom Data Model tab, click New Custom Object.
              1. Enter an appropriate Object label.
              2. Update the Object API name to match the object label.
              3. Select the fields needed in the custom object and update the field labels and data types as required.

                After you save the custom object, you can’t change the field properties.

              4. Save your changes. A confirmation appears with an arrow connecting the fields.
            5. Click Done. The data mapper opens. Your source DLOs are on the left, and the target DMOs are on the right.
            6. Select the field to map, and click the related field in the DMO.

              Here are some recommended field mappings for profile data.

              • Email address maps to Email Address
              • First name maps to First Name
              • Last name maps to Last Name
              • Customer ID or Unique ID (primary key) maps to External Record ID
              • Customer ID or Unique ID (primary key) maps to Party
              • Customer ID or Unique ID (primary key) maps to ContactPointEmail ID
              • Customer ID or Unique ID (primary key) maps to Individual ID (primary key)

              You must map the party-related fields. The Party attribute connects all the pieces of information and helps Data Cloud identify that they all belong to the same person.

              Here are some recommended field mappings for engagement data.

              • Date-time stamp maps to Engagement date time
              • Email address maps to Individual
              • Product ID maps to External record ID
              • Product name maps to Name
              • Purchase price maps to Product Order Event Type
              • Unique transaction ID (Primary key) maps to Product order engagement (primary key)
            7. If the DMO doesn’t have a field that represents the field in your source data, you can add a field to the DMO.
              1. Next to the unmapped fields, click the arrow and select Add New Field.
              2. Enter a field label or display name.
                The Field API Name is automatically completed with a suggestion based on the naming convention.
              3. Select the field data type that’s compatible with the source field’s data type.
              4. Save your changes.
            8. After saving the DMO field mappings, click Save.
            9. Make sure that the data streams and transforms process is successfully‌ completed. If not, refresh the data manually.

            Create a DMO for Match Keys

            Combine multiple fields into a single DMO that can be used as match keys to match records between the two parties. To not expose PII, you must hash personal identifiers using the SHA256 algorithm. The algorithm transforms data to lowercase and removes white spaces.

            Required Editions

            User Permissions Needed
            To use batch transforms Data Cloud Architect permission set

            Using multiple identifiers to link the data of both parties in a collaboration increases the chance of finding a match. Use unique values like email ids, phone numbers or ID numbers.

            1. In Data Cloud, on the Data Transforms tab, click New. If the Data Transforms tab isn’t visible, click More and select Data Transforms.
            2. Select Batch Data Transform, and click Next.
            3. For the data source, select Data Model Objects.
            4. Select the data space to transform, and click Next.
            5. Click Add Input Data, and select the Contact Point Email DMO, to include the email address as a match key.
            6. Select the Party and Email Address columns.
            7. Click Next.
            8. Click the Add Node icon, and select Transform as the node type.
              The selected columns are shown in the preview window.
            9. Create a column that contains the type of data in the DMO.
              1. Click the function icon (fx) and select Custom Formula.
              2. Enter a Transformation Name.
              3. In the text pane, delete the placeholder text Enter your formula… and enter ‘HEM’ to denote hashed email.
              4. For Output Type, select Text, and retain the default value in the Length field.
              5. Enter the column label as Type and the API name as Type__c.
              6. Click Apply.
                This function creates a Type column for all the fields in the Contact Point Email DMO with the value as HEM.
            10. Apply the SHA2 function to hash the data.
              1. Click the function icon (fx) and select Custom Formula.
              2. Enter a Transformation Name.
              3. Search for and select SHA2 as the function.
              4. Delete the placeholder text field, and then search for and select the Email Address column.
              5. For the bitlength value, enter 256.
                The function appears as sha2(ssot__EmailAddress__c, 256)
              6. For Output Type, select Text and enter 256 for the length.
              7. Enter the column label as HashedContact and the API name as HashedContact__C to denote the column that stores the hashed values.
              8. Preview the transform to verify that the email address field is hashed correctly, and then click Apply.
            11. After creating a column with hashed email IDs, remove the column with actual email IDs from the DMO.
              1. Click the Drop Columns icon.
              2. Search for and select the Email Address column and click Apply. 
            12. Add a universally unique identifier string for each record.
              1. Click the function icon (fx) and select Custom Formula.
              2. Search for and select UUID as the function.
              3. For Output Type, select Text, and retain the default value in the Length field.
              4. Enter the column label as ID and the API name as ID__C.
              5. Click Apply.
            13. Apply the same transform to the Contact Point Phone DMO and any other DMO that you want to include as a match key.
              1. Click the Add Input Data icon and select the DMO. 
              2. Create a column that contains the type of data in the DMO. For the Contact Point Phone DMO, enter the value for the Type field as ‘HPH’ to denote hashed.
              3. Apply the SHA2 function to hash the data.
              4. Remove the column with actual email IDs from the DMO.
              5. Add a universally unique identifier string for each record.
            14. Combine the transforms using the Append Node.
            15. Collapse the transformation window and add an output node to the transformation.
            16. Create a DMO for the output.
              1. Select Create New.
              2. For Write Mode, select Replace.
              3. Enter an object name to identify the object that stores the hashed values.
              4. Update the Object API name to match the object name.
              5. Select Contact Point Email ID as the primary key and Key Qualifier Contact Point Email ID as the key qualifier.
              6. Click Apply.
            17. Click Save.
            18. On the Data transform home page, select the transform you created and click Run Now.
              You can also choose to schedule the transform to run at specific intervals.
              After the transform runs, the hashed data is stored in the output DMO.

            Map Output DMO to Individual DMO

            Add a relationship between the output DMO with the hashed data and the Individual DMO.

            Required Editions

            User Permissions Needed
            To map data Data Cloud Architect permission set
            1. In Data Cloud, go to the Data Model tab.
            2. Search for and select the output DMO with the hashed data. If you can’t find the DMO, change the List View from Mapped to All.
            3. On the Relationships tab, click Edit.
            4. Click New Relationship and enter this information. 
              1. For Field, select Party.
              2. For Cardinality, select N:1.
              3. For Related Object, select Individual.
              4. For Related Field, select Individual ID.
            5. Click Save. 

            (Optional) Create Identity Resolution Rules

            To link multiple sources of data about the same person or account into a unified profile, create identity resolution rules. The unified data is consolidated in the Unified Individual DMO.

            Required Editions

            User Permissions Needed
            To create identity resolution rules Data Cloud Architect permission set
            1. Create identity resolution rulesets.
            2. Configure identity resolution match rules.
            3. Configure reconciliation rules.
            4. On your ruleset record home page, click Run Ruleset.
            5. (Optional) To run the ruleset every 24 hours, configure real-time matching.

            Create a Segment

            You can only share segments in a clean room. Create segments based on the Individual or Unified Individual DMO. Each segment must contain a unique segment name and match key.

            Required Editions

            User Permissions Needed
            To create a segment One of these permission sets: Data Cloud Architect, Data Cloud Activation Manager, or Data Cloud Activation Specialist.
            1. Create a segment.
            2. (Optional) For more complex segment criteria, use the Segment Canvas to build segment rules.
            3. Publish a segment.
             
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