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FHIR-dbt-utils is a dbt package. If you are new to dbt then we reccommend browsing the dbt online documentation and training courses. The following resources are a good place to start:
- dbt BigQuery adapter 1.2.0+ installed on your computer
- A
Google Cloud project
where you have
bigquery.dataEditor
andbigquery.user
permissions - The gcloud command line interface for authentication
- A dbt project in which to load the fhir-dbt-utils package
- dbt Spark adapter 1.2.0+ installed on your computer
- A Spark installation with a thriftserver running
- A dbt project in which to load the fhir-dbt-utils package
-
Add this package to your
packages.yml
file:packages: - package: google/fhir_dbt_utils version: 1.0.0
If you are unfamiliar with dbt packages then you can learn more here.
-
Run the following command in your terminal to install the package:
dbt deps
-
By default, this package points to source data from the BigQuery Synthea Generated Synthetic Data in FHIR public dataset. You can test running your project over this dataset by leaving the defaults unchanged. To analyze your own data, follow the instructions below for your data warehouse.
You can export data to BigQuery from a Google Cloud FHIR store by following the instructions in Storing healthcare data in BigQuery. Once your FHIR data is in BigQuery you can point the project variables to it by editing the
dbt_project.yml
file:- database: The name of a Google Cloud project which contains your FHIR BigQuery dataset. For example, bigquery-public-data.
- schema: The name of your FHIR BigQuery dataset. For example, fhir_synthea.
- timezone_default: The IANA time-zone name. For example, Europe/London.
You can use the https://github.com/google/fhir-data-pipes project to create FHIR data for Spark and point the project variables to it by editing the
dbt_project.yml
file:- database: Leave empty for Spark.
- schema: The name of your Spark schema. For example, fhir_synthea.