Tuva Claims Demo

🧰 What does this project do?

The Tuva Claims Demo provides a quick and easy way to run the Tuva Project with synthetic demo data. By default, the project will run with built-in sample data of 100 patients loaded as dbt seeds. If you want to run the demo project with the full demo data from a data share (available for free), please follow the instructions below under "Running the Project with Full Demo Data".

To set up the Tuva Project with your own claims data or to better understand what the Tuva Project does, please review the ReadMe in The Tuva Project package for a detailed walkthrough and setup.

For information on data models and to view the entire DAG check out our dbt Docs.

🔌 Database Support

• BigQuery
• Redshift
• Snowflake

✅ How to get started

Pre-requisites

1. You have dbt installed and configured (i.e. connected to your data warehouse). If you have not installed dbt, here are instructions for doing so.
2. You have created a database for the output of this project to be written in your data warehouse.

Getting Started

Complete the following steps to configure the project to run in your environment.

1. Clone this repo to your local machine or environment.
2. Update the dbt_project.yml file:
   1. Add the dbt profile connected to your data warehouse.
   2. Update the variable tuva_database to use the new database you created for this project.
3. Run dbt deps to install the package.
4. Run dbt build to run the entire project with the built-in sample data.

Running the Project with Full Demo Data

Complete the following additional steps to configure the project to run with the full demo data from one of the supported data shares.

AWS Data Exchange (Redshift)

The full demo data is available as a Redshift data product in the AWS Data Exchange. You can learn more about how to access the Data Exchange here.

1. Make sure you are in the US East (N. Virginia) region.
2. Go to the Tuva Project Claims Demo product on the AWS Data Exchange.
3. Select Continue to Subscribe. Once you subscribe, it will take a few minutes for AWS to process the request.
4. Go to the Redshift Console and select your cluster.
5. Go to the Datashare tab and select any database to view your subscriptions.
6. Under Subscriptions to AWS Data Exchange datashares, select tuva_project_claims_demo, and choose Create database from datashare.
7. Specify a database name for the data in the listing.
8. Update the dbt_project.yml file:
   1. Update the variable tuva_database to the database specified in step 7.
   2. Set the variable full_data_override to 'true'.
9. Run dbt deps to install the Tuva package (you only need to do this once per local environment).
10. Run dbt build to run the entire project.

BigQuery

The full demo data is available as a public dataset in BigQuery and can be queried directly.

1. Update the dbt_project.yml file:
   1. Update the variable tuva_database to your Google Cloud project id.
   2. Set the variable full_data_override to 'true'. (Note: This project includes logic to use the public dataset automatically when this variable is set to true.)
2. Run dbt deps to install the Tuva package (you only need to do this once per local environment).
3. Run dbt build to run the entire project.

Snowflake Marketplace

The full demo data is available in the Snowflake Marketplace. You can learn more about how to access Snowflake Marketplace listings here.

1. Go to the Tuva Project Claims Demo listing on the Snowflake Marketplace.
2. Select Get.
3. Specify a database name for the data in the listing.
4. (Optional) Add roles to grant access to the database created from the listing.
5. Update the dbt_project.yml file:
   1. Update the variable tuva_database to the database specified in step 3.
   2. Set the variable full_data_override to 'true'.
6. Run dbt deps to install the Tuva package (you only need to do this once per local environment).
7. Run dbt build to run the entire project.

🙋🏻‍♀️ How is this project maintained and can I contribute?

Project Maintenance

The Tuva Project team maintaining this project only maintains the latest version of the project. We highly recommend you stay consistent with the latest version.

Contributions

Have an opinion on the mappings? Notice any bugs when installing and running the project? If so, we highly encourage and welcome feedback! While we work on a formal process in Github, we can be easily reached on our Slack community.

🤝 Community

Join our growing community of healthcare data practitioners on Slack!