Explain raw tables and materialized views in Profiles Sync docs

src/unify/profiles-sync/tables.md

@@ -3,15 +3,38 @@ title: Profiles Sync Tables and Materialized Views
 plan: unify
 ---
 
-Through Profiles Sync, Segment provides data sets and models that can help you enrich customer profiles using any warehouse data available to you.
+Through Profiles Sync, Segment provides data sets and models to help you enrich customer profiles using your warehouse data.
 
-Using a practical example of how Segment connects and then merges anonymous profiles, this page explains the tables that Segment lands, as well as the tables you materialize as part of Profiles Sync.
+This page compares raw tables and materialized views, explaining their roles and use cases. It also outlines the tables Segment lands and the tables you can materialize as part of Profiles Sync.
+
+## Understanding raw tables and materialized views
+
+Profiles Sync creates two types of tables in your data warehouse: raw tables and materialized views. These tables help you work with profile and event data at different levels of detail.
+
+- Raw tables store unprocessed event-level data and capture all updates and changes as they occur.
+- Materialized views take data from raw tables and organize it into a streamlined view of profile traits, identifiers, and merges.
+
+The following table shows how raw tables map to their corresponding materialized views:
+
+| Raw table                     | Materialized view  | Description                                                   |
+| ----------------------------- | ------------------ | ------------------------------------------------------------- |
+| `id_graph_updates`            | `profile_merges`   | Tracks changes in profile merges across the identity graph.   |
+| `external_id_mapping_updates` | `user_identifiers` | Tracks external IDs associated with user profiles.            |
+| `profile_traits_updates`      | `user_traits`      | Tracks changes to user profile traits (like names or emails). |
+
+Raw tables are best for detailed, event-level analysis or debugging specific updates in the identity graph. They show every single change and event in your Profiles Sync pipeline.
+
+Materialized views are better for reporting, analytics, and when you need an up-to-date view of profile traits or identifiers. Materialized views reduce complexity by summarizing data from the raw tables.
+
+For example, if you want to debug why a specific profile trait was updated, you'd look at the `profile_traits_updates` raw table. But if you want to see the current profile data for a marketing campaign, you'd probably opt for the `user_traits` materialized view.
 
 ## Case study: anonymous site visits lead to profile merge
+
+This section uses a practical example of how Segment connects and merges anonymous profiles to illustrate how Profiles Sync populates and updates its tables. 
 
-To help illustrate the possible entries and values populated into Profiles Sync tables, view the event tabs below and consider the following scenario.
+Explore the following event tabs to learn how these examples result in profile creation and merging.
 
-Suppose the following four events lead to the creation of two separate profiles:
+Suppose these four events lead to the creation of two separate profiles:
 
 {% codeexample %}
 {% codeexampletab Event 1 %}
@@ -75,6 +98,7 @@ Initially, Segment generates two profiles for the first three calls. In the fina
 Profiles Sync tracks and provides information about these events through a set of tables, which you’ll learn about in the next section.
 
 
+
 ## Profile raw tables 
 
 Profile raw tables contain records of changes to your Segment profiles and Identity Graph over time. 
@@ -83,7 +107,6 @@ With raw tables, you have full control over the materialization of Profiles in y
 
 Raw tables contain complete historical data when using historical backfill.
 
-
 ### The id_graph_updates table
 
 The `id_graph_updates` table maps between the following: