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The Tuva Project is open source software that cleans and transforms messy healthcare data. It does 2 main things:

1. Normalizes data into a common quality-tested format
2. Enriches data with high-level concepts relevant for healthcare

1. You have healthcare data (e.g. EHR, claims, lab, HIE, etc.) in a data warehouse
2. You have dbt installed and configured (i.e. connected to your data warehouse)

Here are instructions for installing dbt.

Execute the following steps to load all seed files, build all data marts, and run all data quality tests in your data warehouse:

1. Clone this repo to your local machine or environment
2. Create a database called 'tuva' in your data warehouse
   • note: this is where data from the project will be generated
3. Create source data tables in your data warehouse
   • note: these tables must match table names and column names exactly as in source.yml
4. Configure dbt_project.yml
   • profile: set to 'tuva' by default - change this to an active profile in the profile.yml file that connects to your data warehouse
   • vars: configure source_name, source database name, and source schema name
5. Run project
   1. Navigate to the project directory in the command line
   2. Execute "dbt build" to create all tables/views in your data warehouse

Don't see a model or specific metric you would have liked to be included? Notice any bugs when installing and running the package? If so, we highly encourage and welcome contributions to this package!

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This package has been tested on Snowflake and Redshift. We are planning to expand testing to BigQuery in the near future.