diff --git a/CHANGELOG.md b/CHANGELOG.md
index 306f972..911fadd 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -14,8 +14,10 @@
   - If you would like to override these updates, you can also manually disable the `fivetran_platform_using_transformations` variable by setting it to False in your project.yml
 
 ## Documentation Updates
-  - Included documentation about the `transformation_runs` source table and the aggregated `*_model_run` fields.
-  - Added information about manually configuring the `fivetran_platform_using_transformations` variable in the [DECISION LOG.](https://github.com/fivetran/dbt_fivetran_log/blob/main/DECISIONLOG.md)
+- Included documentation about the `transformation_runs` source table and the aggregated `*_model_run` fields.
+- Added information about manually configuring the `fivetran_platform_using_transformations` variable in the [DECISION LOG.](https://github.com/fivetran/dbt_fivetran_log/blob/main/DECISIONLOG.md)## Documentation
+- Added Quickstart model counts to README. ([#145](https://github.com/fivetran/dbt_fivetran_log/pull/145))
+- Corrected references to connectors and connections in the README. ([#145](https://github.com/fivetran/dbt_fivetran_log/pull/145))
 
 ## Under the Hood
 - Added `transformation_runs` seed data in `integration_tests/seeds/`.
diff --git a/README.md b/README.md
index cf7b3c6..b858a7a 100644
--- a/README.md
+++ b/README.md
@@ -6,7 +6,7 @@
         <img src="https://img.shields.io/badge/License-Apache%202.0-blue.svg" /></a>
     <a alt="dbt-core">
         <img src="https://img.shields.io/badge/dbt_Core™_version->=1.3.0_<2.0.0-orange.svg" /></a>
-    <a alt="Maintained?">
+    <a alt="Maintained?"> 
         <img src="https://img.shields.io/badge/Maintained%3F-yes-green.svg" /></a>
     <a alt="PRs">
         <img src="https://img.shields.io/badge/Contributions-welcome-blueviolet" /></a>
@@ -16,14 +16,13 @@
 </p>
 
 ## What does this dbt package do?
-- Generates a comprehensive data dictionary of your Fivetran Platform connector (previously called Fivetran Log) data via the [dbt docs site](https://fivetran.github.io/dbt_fivetran_log/)
-
+- Generates a comprehensive data dictionary of your Fivetran Platform connection (previously called Fivetran Log) data via the [dbt docs site](https://fivetran.github.io/dbt_fivetran_log/)
 - Produces staging models in the format described by [this ERD](https://fivetran.com/docs/logs/fivetran-platform#schemainformation) which clean, test, and prepare your Fivetran data from our free [Fivetran Platform connector](https://fivetran.com/docs/logs/fivetran-platform) and generates analysis ready end models.
-- The above mentioned models enable you to better understand how you are spending money in Fivetran according to our [consumption-based pricing model](https://fivetran.com/docs/usage-based-pricing) as well as providing details about the performance and status of your Fivetran connectors. This is achieved by:
-    - Displaying consumption data at the table, connector, destination, and account levels
+- The above mentioned models enable you to better understand how you are spending money in Fivetran according to our [consumption-based pricing model](https://fivetran.com/docs/usage-based-pricing) as well as providing details about the performance and status of your Fivetran connections. This is achieved by:
+    - Displaying consumption data at the table, connection, destination, and account levels
     - Providing a history of measured free and paid monthly active rows (MAR), credit consumption, and the relationship between the two
-    - Creating a history of vital daily events for each connector
-    - Surfacing an audit log of records inserted, deleted, an updated in each table during connector syncs
+    - Creating a history of vital daily events for each connection
+    - Surfacing an audit log of records inserted, deleted, an updated in each table during connection syncs
     - Keeping an audit log of user-triggered actions across your Fivetran instance
 
 <!--section="fivetran_platform_transformation_model"-->
@@ -32,19 +31,25 @@ Refer to the table below for a detailed view of all tables materialized by defau
 
 | **Table**                  | **Description**                                                                                                                                               |
 | -------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| [fivetran_platform__connector_status](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__connector_status)        | Each record represents a connector loading data into a destination, enriched with data about the connector's data sync status.                                          |
-| [fivetran_platform__mar_table_history](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__mar_table_history)     | Each record represents a table's free, paid, and total volume for a month, complete with data about its connector and destination.                             |
+| [fivetran_platform__connector_status](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__connector_status)        | Each record represents a connection loading data into a destination, enriched with data about the connection's data sync status.                                          |
+| [fivetran_platform__mar_table_history](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__mar_table_history)     | Each record represents a table's free, paid, and total volume for a month, complete with data about its connection and destination.                             |
 | [fivetran_platform__usage_mar_destination_history](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__usage_mar_destination_history)    | Table of each destination's usage and active volume, per month. Includes the usage per million MAR and MAR per usage. Usage either refers to a dollar or credit amount, depending on customer's pricing model. Read more about the relationship between usage and MAR [here](https://www.fivetran.com/legal/service-consumption-table).                             |
-| [fivetran_platform__connector_daily_events](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__connector_daily_events)    | Each record represents a daily measurement of the API calls, schema changes, and record modifications made by a connector, starting from the date on which the connector was set up.                            |
-| [fivetran_platform__schema_changelog](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__schema_changelog)    | Each record represents a schema change (altering/creating tables, creating schemas, and changing schema configurations) made to a connector and contains detailed information about the schema change event.                           |
-| [fivetran_platform__audit_table](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__audit_table)    | Replaces the deprecated [`_fivetran_audit` table](https://fivetran.com/docs/getting-started/system-columns-and-tables#audittables). Each record represents a table being written to during a connector sync. Contains timestamps related to the connector and table-level sync progress and the sum of records inserted/replaced, updated, and deleted in the table.                             |
+| [fivetran_platform__connector_daily_events](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__connector_daily_events)    | Each record represents a daily measurement of the API calls, schema changes, and record modifications made by a connection, starting from the date on which the connection was set up.                            |
+| [fivetran_platform__schema_changelog](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__schema_changelog)    | Each record represents a schema change (altering/creating tables, creating schemas, and changing schema configurations) made to a connection and contains detailed information about the schema change event.                           |
+| [fivetran_platform__audit_table](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__audit_table)    | Replaces the deprecated [`_fivetran_audit` table](https://fivetran.com/docs/getting-started/system-columns-and-tables#audittables). Each record represents a table being written to during a connection sync. Contains timestamps related to the connection and table-level sync progress and the sum of records inserted/replaced, updated, and deleted in the table.                             |
 | [fivetran_platform__audit_user_activity](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__audit_user_activity)    | Each record represents a user-triggered action in your Fivetran instance. This table is intended for audit-trail purposes, as it can be very helpful when trying to trace a user action to a [log event](https://fivetran.com/docs/logs#logeventlist) such as a schema change, sync frequency update, manual update, broken connection, etc.                             |
+
+### Materialized Models
+Each Quickstart transformation job run materializes 19 models if all components of this data model are enabled. This count includes all staging, intermediate, and final models materialized as `view`, `table`, or `incremental`.
 <!--section-end-->
 
 ## How do I use the dbt package?
 ### Step 1: Pre-Requisites
-- **Connector**: Have the Fivetran Platform connector syncing data into your warehouse.
-- **Database support**: This package has been tested on **BigQuery**, **Snowflake**, **Redshift**, **Postgres**, **Databricks**, and **SQL Server**. Ensure you are using one of these supported databases.
+
+To use this dbt package, you must have the following:
+
+- The Fivetran Platform connection syncing data into your destination.
+- A **BigQuery**, **Snowflake**, **Redshift**, **Postgres**, **Databricks**, or **SQL Server**. destination.
 
 #### Databricks Dispatch Configuration
 If you are using a Databricks destination with this package you will need to add the below (or a variation of the below) dispatch configuration within your `dbt_project.yml`. This is required in order for the package to accurately search for macros within the `dbt-labs/spark_utils` then the `dbt-labs/dbt_utils` packages respectively.