Steps Completed by Patients

The following table describes each step in the patients flow, and explains which steps usually need to be edited for your data.

If you need to make changes to the mastering flow beyond those described in this documentation, contact Support at [email protected] for assistance.

Usually Requires Changes	Step	Description
✅	Add Data	You verify that source data meets both general requirements and template-specific requirements. Then, you add source data.
✅	Align to Patients Mastering Data Model	You map input columns to attributes in the supplied schema. If you add attributes to the unified schema, you will need to update the following steps, as described in the rows below, to ensure that these attributes appear in your final mastered entities: Consolidate Records Configure Attributes
❌	Create `tamr_record_id`	This transformation step ensures that each source record has a unique primary key across all source datasets by adding a new primary key field: `tamr_record_id`. The `tamr_record_id` is a 128-bit hash value of the source dataset name and the source primary key. See the Tamr Core documentation for a description of the function used to generate the hash value. Important: If records within the same source dataset have duplicate primary key values, the `tamr_record_id` value for those records will also be duplicates. If you mapped an empty placeholder column to the `trusted_id` attribute, add the following transformation: `SELECT *, '' as trusted_id;`.
❌	Prepare Data for Address Enrichment	This step transforms the data in the unified dataset to match the expected inputs for the address enrichment service.
❌	Enrich Address	This step standardizes and validates address information, and enriches addresses with latitude, longitude, and detailed address information. See Address Standardization, Validation, and Geocoding.
❌	Prepare Address Fields	This step transforms the data in address fields in the unified dataset to prepare for clustering.
❌	Prepare Data for Phone Enrichment	This step transforms the data in the unified dataset to match the expected inputs to the phone number data quality service included in the mastering flow. This step replaces empty country values in source records with the country returned by the Enrich Address step.
❌	Enrich Phone	This step standardizes and validates phone number information. See Phone Number Enrichment.
❌	Prepare for Clustering	This step transforms the data in the unified dataset to create the fields used by the trained clustering model to identify similar and matching records. The fields created as input to the model are prefixed with `ml_`. Many of these `ml_` fields are created as arrays of unified source fields and fields added by the enrichment services. The model identifies the most similar values across the arrays and assigns weights based on these similarities.
❌	Apply Clustering Model	This step groups records that refer to the same entity into a cluster, using the trained model. See Features of Patients.
✅	Consolidate Records	This step applies rules to produce a single record, called the mastered entity record, that best represents a cluster. For most fields, these rules select the most common value from the clustered records. Additionally, this step adds a Tamr ID (`tamr_id`) to each mastered entity record. The Tamr ID is a unique, persistent id. If you added new attributes in the Schema Mapping step, add lines in the transformations to tell Tamr Cloud what value to set for each attribute when creating the mastered entity. See Modifying Record Consolidation Transformations.
✅	Configure Attributes	You configure how mastered entity attributes appear in Tamr Cloud and published datasets See Configuring Data Display.