How to Use Neuron against Snowflake with Azure Synapse

April 11, 2024

In our last post, we guided you through the process of deploying Neuron on Azure Synapse. Today, we'll build upon that discussion by demonstrating how to connect Neuron to a Snowflake Data Warehouse. This setup allows you to leverage all the advantages Snowflake offers for analyzing your population health data.

Snowflake offers a cloud-based data warehousing service that enables businesses to store and analyze data using cloud infrastructure. This service offers a flexible and scalable data storage solution designed to manage large amounts of data. By separating computing and storage resources, Snowflake allows users to adjust their resource levels as needed and only pay for what they use.

Let’s get started …

1. Configure Neuron database for Snowflake

To connect with Snowflake, you must use the Neuron Snowflake database driver, which enables Neuron to access and interact with your Snowflake Data Warehouse. Additionally, you will need to provide various connection details including the database name, schema, warehouse, username, and password.

Note: For enhanced security, consider using Azure Key Vault to securely store your Snowflake password.

2. Run Neuron against your Snowflake Data Warehouse

You will operate Neuron in the same manner as you would in Azure Synapse. However, instead of pulling data from your Azure Data Lake, it will connect to your Snowflake Data Warehouse to perform all calculations. For your Snowflake end users, this transition will be seamless. Neuron serves as the central processing unit for your population health metrics. It will access all the clinical data in Snowflake, conduct the necessary computations, and then write the results back to Snowflake.

3. Review Neuron results in Snowflake Worksheet

After Neuron finishes processing, it stores the results back into Snowflake. You can view these results using SQL in a Snowsight Worksheet.  Here’s a review of a couple key output tables that Neuron produces for analysts to review.

  • Metric Details: This table offers detailed patient-level information. You can query specific patients by measurement to determine their inclusion in the eligible population, compliance with the numerator, meeting of exclusion criteria, and to review audit data that explains their involvement in certain events.
  • Metric Rates: This table provides a consolidated summary of all metrics, detailing counts for each category, such as the total number of eligible patients, those compliant with the numerator, and those excluded as required, among others.


This was a guide on integrating Neuron with Snowflake Data Warehouse to leverage the benefits of Snowflake for value-based care data analysis. Snowflake is a cloud-based data warehousing service that offers flexible and scalable data storage, allowing businesses to efficiently store and analyze large amounts of data.

  1. Configure Neuron for Snowflake: To connect Neuron to Snowflake, you must use the Neuron Snowflake database driver and provide connection details like the database name, schema, warehouse, username, and password.
  2. Run Neuron on Snowflake: Neuron will operate similarly to its function on Azure Synapse but will point to and process data from the Snowflake Data Warehouse instead of Azure Data Lake.
  3. Review Results in Snowflake Worksheet: Post-processing, Neuron stores results in Snowflake, which can be viewed using SQL in a Snowsight Worksheet. The results include detailed patient metrics and a summary of all measures, such as patient eligibility, compliance, and exclusions.

Contact us today to get a more in-depth demo and discuss how Neuron can help your organization with your value-based care needs.