Snowflake for
Data Mesh
Deliver domain-driven ownership with self-service infrastructure as a platform.
Why
Snowflake?
Self-service infrastructure as a platform
Enable domain teams to work with tools and languages of their choice, and scale resources independently with Snowflake’s elastic performance engine.
Collaboration on data products
Seamlessly collaborate and share data products across clouds and regions without copying or ETL.
Federated governance
Use Snowflake’s native cross-cloud governance controls to strike the right balance between domain ownership and centrally managed governance.
Customer
Testimonials
Since shifting to data mesh with Snowflake, 5.5x more people are using data across the business on a regular basis.
Abhi Sivasailam
Head of Growth and Analytics
Using Snowflake has allowed us to simplify our process in how we set up each domain and improved the teams’ autonomy over their own data and ETL process.
Riya Singh
Business Insights Manager
With Snowflake, we reduced run times of complex data queries and large extractions for the SCM control tower from hours to minutes. It has transformed how we contribute value-adding to supply-chain management.
Susanne Berg
Head of Healthineers Data Cloud
Featured
Content
How to Knit Your Data Mesh with Snowflake
In this white paper, learn about the most critical Snowflake capabilities for a data mesh and common architecture patterns used by customers to implement a self-service data platform that supports distributed domains.
The Snowflake Approach to Data Mesh
In this webinar, learn how key capabilities of the Snowflake platform are uniquely suited to support Data Mesh implementations including a live demo.
Resources
Video
Choreograph Uses Snowflake to Build a Data Mesh to Enhance Data Sharing Across WPP’s Vast Enterprise
WAYS TO
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Start Your 30-Day
Free Trial
Try Snowflake free for 30 days and experience the Data Cloud that helps eliminate the complexity, cost, and constraints inherent with other solutions. Available on all three major clouds, Snowflake supports a wide range of workloads, such as data warehousing, data lakes, AI and machine learning.