Update README.md

README.md

@@ -5,27 +5,30 @@ This dbt model is based on the premise that three kids are playing a video game
 
 Overall it has some simple dbt models along with related tests. Its purpose is to provide users with some quick examples of dbt schema and data tests. 
 
-In order to create this dbt model, you will want to install [dbt](https://docs.getdbt.com/docs/introduction) before you clone this repository
+**Note:** This project uses BigQuery to contain the dbt project's data, so the instructions are specific to BigQuery database configuration.
 
-This project requires the setup of a PostgreSQL BigQuery server where you will be able to run these seeds, models and tests. I used [this guide](https://cloud.google.com/sql/docs/postgres/create-instance#create-2nd-gen) to set up my PostgreSQL container on BigQuery with dbt.
+### Before Running the Project (Prerequisites)
+In order to create this dbt model, you will want to **install [dbt]**(https://docs.getdbt.com/docs/introduction) before you clone this repository
 
-The project has custom configuration instructions for the dbt profiles.yml file, which is covered in [dbt documentation](https://docs.getdbt.com/reference/profiles.yml/) if the tutorial isn't enough.
+This project requires the **setup of a PostgreSQL BigQuery server** where you will be able to run these seeds, models and tests. I used [this guide](https://cloud.google.com/sql/docs/postgres/create-instance#create-2nd-gen) to set up my PostgreSQL container on BigQuery with dbt.
+
+The project has **custom configuration instructions for the dbt profiles.yml file**, which is covered in [dbt documentation](https://docs.getdbt.com/reference/profiles.yml/) if the tutorial isn't enough.
 
 ### How to Run the Project
 #### Step 1.
-Create a Big Query project, and subsequently a PostgreSQL Resource inside the project. 
+Create a Big Query project (Referenced above), and subsequently a PostgreSQL Resource inside the project. 
 
 To run this project, you'll need the following from your Big Query SQL instance: 
 - The instance connection name (usually something like "jenny-cassette-8675309"), called "project" in profiles.yml
 - The Service Account JSON key for your specific project (a downloadable JSON key you'll reference), called a "keyfile" in profiles.yml
-- The dataset name (usually "postgres" automatically when you create a PostgreSQL instance in Big Query, you should not have to change this)
+- The dataset (schema) name
 
 #### Step 2.
 Clone this repo to your machine. 
 
-Now, you'll bring your Big Query values into profiles.yml and sources.yml.
+Bring your Big Query values into profiles.yml (local under the hidden .dbt/ folder) and the project's [sources.yml](https://github.com/corissawex/dbtTestExamples/blob/86d41367884fa8d27383f099e0132b7f730b9ba4/models/1-source/sources.yml#L6).
 
-Sources.yml is easy; you just need to enter the database name (instance connection name).
+Sources.yml is quick; follow the comments and enter the database name (instance connection name) and the schema (dataset) name.
 
 Profiles.yml is a little more complex so you should just copy and paste the below profile, then enter the right values for your Big Query keyfile and project.
 
@@ -70,6 +73,10 @@ Alternatively, you can choose to run just schema or data tests using these comma
     dbt test --data
 
     dbt test --schema
+
+Or, run all tests for a specific model: 
+
+    dbt test --models statistics
 
 ### I already know dbt, can I just jump in? 
 Sure! Just be sure to connect Big Query to this dbt project after you've cloned it, and reconfigure any custom changes.