Healthcare Data Governance: Snowflake, Databricks, and Azure Synapse

Comparing Data Governance and Capabilities in Snowflake, Databricks, and Azure Synapse

Oct 10, 2023

Introduction:

In the evolving landscape of healthcare, data governance emerges as a critical facet in ensuring data quality, security, and compliance. The trio of leading Azure platforms; Snowflake, Databricks, and Synapse each present a compelling option to navigate the complex healthcare governance terrain. This article will delve into the data governance capabilities of these platforms in the context of healthcare.

Snowflake: Snowflake's robust governance features are instrumental in securing and managing healthcare data. Its column and row-level security, along with object tagging, are pivotal in ensuring the confidentiality and integrity of sensitive patient information. Moreover, its data classification and access history functionalities are crucial for compliance with healthcare regulations like HIPAA.

Databricks: Databricks facilitates an integrated environment for managing and analyzing healthcare data. Its Delta Lake and Delta Engine provide a reliable foundation for data quality and integrity, which are crucial for accurate diagnoses and treatment plans. The platform's data ingestion, governance, and discovery features are paramount in maintaining a well-organized, compliant, and easily accessible data repository, fostering enhanced patient care and operational efficiency.

Synapse: Synapse embodies a holistic approach to healthcare data governance with its Synapse SQL, Spark, and Pipelines. It provides a seamless interface for querying, analyzing, and managing data, ensuring adherence to regulatory standards. The integration with Azure Data Share, Azure Machine Learning, and Power BI further amplifies its governance capabilities, providing a comprehensive solution for healthcare data management, analysis, and compliance.

Comparing Governance Capabilities:

When juxtaposed, each platform presents unique strengths in data governance. Snowflake excels in security features, Databricks in data management and analytics, while Synapse provides a well-rounded solution with strong integration capabilities. The choice among these would hinge on your organization’s specific governance, analytic, and compliance requirements. It's also essential to highlight the growing need for a platform approach to that not only supports multi-tenant but also utilizes a combination these three services in a manner that leverages their strengths efficiently.

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Snowflake:

Snowflake offers a plethora of data governance features suitable for healthcare, including:

Column-level Security: This allows the application of a masking policy to a column within a table or view, ensuring sensitive data remains protected.
Row-level Security: This feature enables the application of a row access policy to a table or view to determine which rows are visible in query result .
Object Tagging and Tag-based Masking Policies: These features facilitate the tracking and protecting of sensitive data for compliance, discovery, protection, and resource usage.
Data Classification: This is crucial for categorizing potentially personal and/or sensitive data to support compliance and privacy regulations.
Access History: It allows the auditing of the user access history, which is crucial for compliance and auditing purposes.
Object Dependencies: This feature enables the auditing of how one object references another object by its metadata(1).

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Databricks:

Databricks, as a lakehouse cloud data platform, also presents a host of data governance features including:

Delta Lake: An open-source storage layer bringing reliability and performance to data lakes by enabling ACID transactions, schema enforcement, and time travel which are crucial for data integrity and auditing.
Data Management in Databricks SQL: It allows the management of data sources, tables, views, functions, and databases using SQL commands or a graphical user interface, which is pivotal for data governance.
Data Ingestion and Governance: This feature allows the ingestion of data from various sources and applying quality checks, transformations, and enrichment to the data using SQL or Python, ensuring data quality and compliance.
Data Discovery, Annotation, and Exploration: This is facilitated through Unity Catalog, aiding in data discovery, cataloging, tagging, commenting, searching, and browsing data assets (2,3,4,5).

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Azure Synapse:

Azure Synapse integrates well with the healthcare domain, offering governance features like:

Healthcare Database Templates: These are industry-specific schema definitions in Azure Synapse that accelerate the building of analytics-infused industry applications.
Azure Purview Integration: Azure Purview provides a unified data governance solution to help manage and govern your on-premises, multicloud, and software as a service (SaaS) data, creating a holistic, up-to-date map of your data landscape.
Azure Health Data Services: Azure Synapse is part of the Azure Health Data Services which provides a platform to store, process, and analyze sensitive data while adhering to stringent security and compliance standards.
Synapse Pipelines and Apache Spark Pool: These features in Azure Synapse assist in orchestrating data movement and transformation activities, and in-memory computing for fast validation of data files respectively, which are essential for data governance and performance optimization in healthcare (6,7,8,9)

Conclusion:

The confluence of Snowflake, Databricks, and Synapse on Azure represents a robust framework for healthcare data governance. By leveraging their complementary and individual strengths, healthcare organizations can ensure the quality, security, and regulatory compliance of their data, ultimately contributing to improved patient care and operational excellence.