Snowflake in Healthcare 2023
Streamlining Data Management & Improving Operations in the Cloud

Most interviewed customers report improved operational efficiency after implementing the Snowflake Data Cloud, citing the consolidated data sources, simple maintenance and data management, and easy data loading and access. Additionally, almost 40% of respondents see improved data integration from using the Snowflake Data Cloud as their centralized data platform. Other commonly reported benefits include cost savings, scalability, and the ability to quickly analyze and gain insights into market share, profitability, and cost utilization. 56% of respondents report seeing outcomes either immediately or within a few weeks.

“Running the data in the Snowflake Data Cloud and normalizing it into all of our downstream platforms takes a couple of hours. If we want the same data in Microsoft’s SQL Server product, that process will probably take several days.” —Director

Snowflake customers most frequently highlight how quickly the solution can be adopted as well as its simplicity and user-friendliness, both of which contribute to high customer satisfaction. Users are often enthusiastic to learn how to use the platform as it offers new capabilities without requiring extensive training. Respondents also say that the solution’s similarity with Microsoft SQL Server facilitates quick adoption and streamlined, comprehensive data sharing. Implementations are noted for being easy and efficient, enabling some customers to be operational within minutes of going live. The solution’s agility and broad integration capabilities are also seen as highlights.

Data migration is a common challenge for clients using the Snowflake Data Cloud. Healthcare organizations often use multiple third-party vendors and various data sources, and they need a consolidated tool set that supports data ingestion. While Snowflake excels in data transformation, data extraction is not their primary focus, which can make migrating databases to the Snowflake Data Cloud time consuming and difficult. Customers may potentially need to use separate extraction tools. Additionally, achieving integration with Active Directory for single sign-on can be challenging, so customers have to provide a comprehensive guide to enable users to navigate the intricacies of integration with other systems. The lack of internal expertise and guidance from Snowflake is another obstacle that some interviewed customers encounter, leading to underutilization of the platform. Customers want improved engagement and education from Snowflake to leverage the platform’s benefits fully.

Applications: “When the use cases warrant it, we will start looking at buying or subscribing to already built applications. . . . Snowflake’s relatively recent release of Snowpark and its data environment will definitely extend our use of the Snowflake Data Cloud so that we either use existing applications or potentially build some small, niche applications.” —Manager

Data engineering: “Our future plans with Snowflake are to continue to use their system and to grow and expand it across our organization. As we merge with additional entities and bring in their data sets, our environment is going to continue to grow. We are going to have new data sets, data models, and data sources all flowing into the Snowflake Data Cloud. The Snowflake Data Cloud is going to be the single source of truth for all of our downstream applications.” —Director

Data science: “The data science workload in the Snowflake Data Cloud is definitely very interesting to us and is something that we are looking into. Data science capabilities are way too easy with the product, so we don’t need a lot of other tools or products. We can do most of what we need to do within the platform.” —Manager

Target customer
Any organization looking to eliminate data silos (e.g., large IDNs, academic medical centers, small/midsize health systems, etc.)

Healthcare market
Global

Number of employees focused on healthcare
200+

Estimated healthcare revenue
$250M+ ARR

AI
Snowflake accelerates AI/ML workflows by providing one place to gain scalable, real-time access to all data (structured, semi-structured, unstructured) as well as third-party data via the Snowflake Marketplace. Additionally, Snowflake allows for models to be trained and productionized using the language of your choice via Snowpark and Snowpark Container Services. Our flexible compute architecture allows for simple, predictable scaling depending on cost/performance requirements. Snowflake provides a single platform to unify developers, ML operations engineers, and end-consumers with integrated notebooks, Snowpark ML Modeling, Snowflake Feature Store, and Model Registry.

Snowflake Healthcare Executive Interview

Jesse Cugliotta,
Global Industry Lead for Healthcare & Life Sciences

What is your background?
I have over 20 years of experience working in data and analytics, with a specific focus on clients in the healthcare and life sciences industries. I lead a global team of sub-industry-focused subject matter experts who drive the strategy for healthcare and life sciences at Snowflake.

What should healthcare organizations know about Snowflake’s investment in and commitment to healthcare?
Our mission is to break down data silos and enable secure data collaboration across healthcare and life sciences organizations and the essential partners and technologies that support them. Snowflake’s Healthcare & Life Sciences Data Cloud is an open, interoperable ecosystem that helps provider, payer, and life sciences organizations overcome fragmented data to improve health outcomes and reduce costs—all while maintaining the highest standards of data governance and privacy.

What are Snowflake’s biggest differentiators?
With Snowflake’s Healthcare & Life Sciences Data Cloud, healthcare organizations have a single, integrated, and cross-cloud data platform that eliminates technical and institutional data silos. This will enable organizations to securely centralize, integrate, and exchange critical and sensitive data at scale. Snowflake ensures high levels of data security and governance, and our built-in capabilities and extended partner network allow organizations to better meet compliance requirements and satisfy industry regulations.

What core outcomes should healthcare customers expect from Snowflake’s solution?
Snowflake healthcare and life sciences customers realize benefits across the value chain. Common use cases include patient 360, SDOH/population health analytics, staff attrition predictions, supply chain optimization, trusted research environments, DICOM analytics, LLM-powered applications, and many others.

What is Snowflake’s revenue model?
With Snowflake, customers can turn compute resources on and off and only pay for what they use. Customers can also take advantage of cost-effective compression in Snowflake to store near unlimited amounts of data and grow their analytics infrastructure with linear cost scalability.

Cloud environment
AWS, Microsoft Azure, GCP

Development platform
SQL, Python, Java, Javascript, Scala, Snowpark Container Services

Database environment
Columnar OLAB SQL

Mobile application environment
Browser based

Security platform
NIST 800-171, SOC 1 Type 2, SOC 2 Type 2, ISO 27001

Confidentiality
HIPAA, BAAs

Data encryption
AES-256 (at rest); TLS (in-transit)

Integration approach
HL7 2.x, FHIR, APIs

HITRUST certification
Yes