Merge pull request #4593 from segmentio/profiles-sync-updates

Update Profiles Sync headers

Author: rchinn1

src/unify/profiles-sync/tables.md

@@ -9,7 +9,7 @@ Using a practical example of how Segment connects and then merges anonymous prof
 
 ## Case study: anonymous site visits lead to profile merge
 
-To help illustrate the possible entries and values populated into Profiles Sync tables, consider the following scenario.
+To help illustrate the possible entries and values populated into Profiles Sync tables, view the event tabs below and consider the following scenario.
 
 Suppose the following four events lead to the creation of two separate profiles:
 
@@ -79,7 +79,7 @@ Profiles Sync tracks and provides information about these events through a set o
 
 Using the events from the profile merge case study, Segment would land the following tables as part of Profiles Sync.
 
-### The `id_graph_updates` table
+### The id_graph_updates table
 
 The `id_graph_updates` table maps between the following:
 
@@ -109,7 +109,7 @@ Segment shows the complete history of every profile. If, later, `profile_1` merg
 
 If you’ll use Profiles Sync to build models, refer to the `id_graph` model, which can help you put together a complete view of a customer.
 
-### The `external_id_mapping_updates` table
+### The external_id_mapping_updates table
 
 This table maps Segment-generated identifiers, like `segment_id`, to external identifiers that your users provide.
 
@@ -127,7 +127,7 @@ The anonymous site visits sample used earlier would generate the following event
 
 In this table, Segment shows three observed identifiers. For each of the three identifiers, Segment outputs the Segment ID initially associated with the identifier.
 
-### `identifies`, `page`, `screens`, and track tables
+### The identifies, page, screens, and track tables
 
 These tables show the instrumented events themselves. Entries in these tables reflect payloads that you instrument according to the Segment spec.
 
@@ -189,11 +189,11 @@ Follow the steps below to change your schema name:
 > To get started with your table materializations, try Segment's [open-source dbt models](https://github.com/segmentio/profiles-sync-dbt){:target="_blank"}, or materialize views with your own tools.
 
 > warning ""
-> Please note that dbt models are in beta and need modifications to run efficiently on BigQuery, Synapse, and Postgres warehouses. Segment is actively working on this feature. 
+> Please note that dbt models are in beta and need modifications to run efficiently on BigQuery, Synapse, and Postgres warehouses. Segment is actively working on this feature.
 
 Every customer profile (or `canonical_segment_id`) will be represented in each of the following tables.
 
-### `id_graph` table
+### The id_graph table
 
 This table represents the current state of your identity graph, showing only where a `segment_id` is now understood to point.
 
@@ -204,9 +204,10 @@ The most recent entry for each `segment_id` from `id_graph_updates` reflects thi
 | `profile_1`            | `profile_1`                      | 2022-05-02 14:01:00     |
 | `profile_2`            | `profile_1`                      | 2022-06-22 10:48:00     |
 
+
 Segment drops most diagnostic information from this table, since it’s designed for reference use. In this case, you’d learn that any data references to `profile_2` or `profile_1` now map to the same customer, `profile_1`.
 
-### `external_id_mapping` table
+### The external_id_mapping table
 
 Use this table to view the full, current-state mapping between each external identifier you’ve observed and its corresponding, fully-merged `canonical_segment_id`.
 
@@ -219,7 +220,7 @@ In the case study example, you’d see the following:
 | `profile_1`                      | `anonymous_id`               | `b50e18a5-1b8d-451c`          | `2022-06-22 10:48:00`  |
 
 
-### `profile_traits` table
+### The profile_traits table
 
 Use the `profile_traits` table for a singular view of your customer. With this table, you can view all custom traits, computed traits, SQL traits, audiences, and journeys associated with a profile in a single row.