Tecton announced a partnership with Snowflake to help
data teams operationalize ML applications. The two companies have collaborated
to integrate both Tecton and Feast with Snowflake's Data Cloud. The joint
solutions provide a simple and fast path to building production-grade features
to support a broad range of operational ML use cases including fraud detection,
product recommendations and real-time pricing.
"Cloud data platforms such as Snowflake Data Cloud have
emerged as a new option to help data science teams build and deploy ML models.
If managed well, these platforms can provide a scalable and governed repository
of data to support feature engineering, model training and ML operations. They
can offer a system of record for feature stores such as Tecton," said Kevin
Petrie, Vice President of Research at Eckerson Group.
The Tecton feature store is a central hub for ML features, the
intelligent data signals that power operational ML models. Tecton allows data
teams to define features as code using Python and SQL. Tecton then automates ML
data pipelines, generates accurate training datasets and serves features online
for real-time inference. With Tecton, data teams can build features
collaboratively using software engineering best practices and share features
across models and use cases. New features can be delivered in minutes without
the need to build bespoke data pipelines.
Snowflake customers can now use Tecton as the interface between the Snowflake
Data Cloud and their ML models. Tecton connects to Snowflake as the central
source of truth for data, computes data transformations and training datasets
on Snowflake using SQL and Snowpark and serves data directly from Snowflake
tables.
Simultaneously, Tecton customers benefit from the speed,
scalability and cost-effectiveness of the Snowflake elastic performance engine.
With Snowflake, ML data pipelines that previously took hours to process can now
be delivered in minutes at a fraction of the cost.
In addition, Tecton and Snowflake have jointly built a Snowflake
connector for Feast, the popular open source feature store which counts
thousands of active users. Snowflake customers can now easily adopt Feast to
operationalize analytic data for model training and online inference.
"Many Tecton and Feast users have adopted Snowflake as the
central source of truth for their analytical data, and want to use Snowflake as
the processing engine for ML features," said Mike Del Balso, co-founder and CEO
of Tecton. "Our Snowflake partnership allows Tecton and Feast users to process
ML data on their Snowflake Data Cloud, with best-in-class efficiency and
reliability."
"We are delighted to partner with Tecton to bring commercial and
open source feature stores to Snowflake's platform," said Torsten Grabs,
Director of Product Management at Snowflake. "Snowflake customers now have the
option to use either Tecton or Feast to build and manage their features for
operational ML."