Bringing Extra AI to Snowflake, the Knowledge Cloud

Maximizing Current Snowflake Investments

Some companies have spent important cash on instruments to stay modern and aggressive. Whereas this may be a wonderful technique for a future-oriented firm, it might show futile in case you don’t maximize the worth of your funding. In line with Flexera¹, 92% of enterprises have a multi-cloud technique, whereas 80% have a hybrid cloud technique.

Integrating completely different methods, knowledge sources, and applied sciences inside an ecosystem may be troublesome and time-consuming, resulting in inefficiencies, knowledge silos, damaged machine studying fashions, and locked ROI. 

The DataRobot AI Platform and the Snowflake Knowledge Cloud present an interoperable, scalable AI/ML resolution and distinctive companies that combine with various ecosystems in order that data-driven enterprises can concentrate on delivering trusted and impactful outcomes.

Extending Snowflake Integration: New Capabilities and Enhancements

To assist clients maximize their Snowflake funding, DataRobot is extending its Snowflake integration to assist clients rapidly iterate, enhance fashions, and full the ML lifecycle with out repeated configuration. 

This consists of: 

1. Supporting Snowflake Exterior OAuth configuration
2. Leveraging Snowpark for exploratory knowledge evaluation with DataRobot-hosted Notebooks and mannequin scoring
3. A seamless person expertise when deploying and monitoring DataRobot fashions to Snowflake
4. Monitoring service well being, drift, and accuracy of DataRobot fashions in Snowflake

“Organizations are on the lookout for mature knowledge science platforms that may scale to the dimensions of their whole enterprise. With the most recent capabilities launched by DataRobot, clients can now assure the safety and governance of their knowledge used for ML, whereas concurrently growing the accessibility, efficiency, and effectivity of information preparation, mannequin coaching, and mannequin observability by their customers,” stated Miles Adkins, Knowledge Cloud Principal, AI/ML at Snowflake. “By bringing the unrivaled AutoML capabilities of DataRobot to the info in Snowflake’s Knowledge Cloud, clients get a seamless and complete enterprise-grade knowledge science platform.”

Full the Machine Studying Lifecycle, With out Repeated Configuration

Connecting to Snowflake

Connect with Snowflake by way of exterior id suppliers utilizing Snowflake Exterior OAuth with out offering person and password credentials to DataRobot. Scale back your safety perimeter by reusing your present Snowflake safety insurance policies with DataRobot.

Be taught extra about Snowflake Exterior OAuth.

Exploratory Knowledge Evaluation 

After we connect with Snowflake, we will begin our ML experiment.

We just lately introduced DataRobot’s new Hosted Notebooks functionality. 

For our joint resolution with Snowflake, which means code-first customers can use DataRobot’s hosted Notebooks because the interface and Snowpark processes the info straight within the knowledge warehouse. This permits customers to work with acquainted Python syntax that will get pushed right down to Snowflake to run seamlessly in a extremely safe and elastic processing engine. They’ll take pleasure in a hosted expertise with code snippets, versioning, and easy atmosphere administration for fast AI experimentation. 

Be taught extra about DataRobot hosted notebooks.

Mannequin Coaching

As soon as the info is ready, customers select their most well-liked method for mannequin growth utilizing DataRobot AutoML by way of the GUI, hosted Notebooks, or each.

When the coaching course of is full, DataRobot will advocate the best-performing mannequin for manufacturing primarily based on the chosen metric and supply an evidence.

Mannequin Deployment

Clients want the pliability to deploy fashions into completely different environments. Deploying to Snowflake reduces infrastructure operations complexity, knowledge switch latency and related prices, whereas enhancing effectivity and offering close to limitless scale.

A brand new Snowflake prediction atmosphere configured by DataRobot will mechanically handle and management the atmosphere, together with mannequin deployment and alternative.

When deploying a DataRobot mannequin to Snowflake, this new seamless integration considerably improves the person expertise, reduces effort and time, and eliminates person errors. 

The automated deployment pushes skilled fashions as Java UDFs, operating scalable inference inside Snowflake, and leveraging Snowpark to attain the info for pace and elasticity, whereas holding knowledge in place.

Mannequin Monitoring

Inside and exterior components have an effect on fashions’ efficiency.

The brand new monitoring job functionality, which is run seamlessly from the DataRobot GUI helps clients make enterprise selections primarily based on predictions and precise knowledge adjustments and govern their fashions at scale.

Over time fashions degrade and require alternative or retraining. The DataRobot MLOps dashboards current the mannequin’s well being, knowledge drift, and accuracy over time and will help decide mannequin accountability.

Be taught extra concerning the new monitoring job and automated deployment.

There’s extra coming

We now have extra thrilling capabilities to share, many associated to the Snowflake integration, which can be introduced on the DataRobot 9.0 launch occasion on March sixteenth. Register right here to be a part of this digital occasion. 

In case you are already a buyer of Snowflake and DataRobot, attain out to your account staff to stand up to hurry on these new options.

Getting Began with DataRobot AI and Snowflake, the Knowledge Cloud

DataRobot and Snowflake collectively provide an end-to-end enterprise-grade AI expertise and experience to enterprises by decreasing complexity and productionizing ML fashions at scale,  unlocking enterprise worth. Be taught extra at DataRobot.com/Snowflake. 

¹ Supply: Flexera 2021 State of the Cloud Report

Concerning the creator

Atalia Horenshtien

International Technical Product Advocacy Lead, DataRobot

Atalia Horenshtien is a International Technical Product Advocacy Lead at DataRobot. She performs an important function because the lead developer of the DataRobot technical market story and works intently with product, advertising and marketing, and gross sales. As a former Buyer Going through Knowledge Scientist at DataRobot, Atalia labored with clients in numerous industries as a trusted advisor on AI, solved advanced knowledge science issues, and helped them unlock enterprise worth throughout the group.

Whether or not chatting with clients and companions or presenting at trade occasions, she helps with advocating the DataRobot story and the best way to undertake AI/ML throughout the group utilizing the DataRobot platform. A few of her talking classes on completely different subjects like MLOps, Time Sequence Forecasting, Sports activities tasks, and use instances from varied verticals in trade occasions like AI Summit NY, AI Summit Silicon Valley, Advertising AI Convention (MAICON), and companions occasions corresponding to Snowflake Summit, Google Subsequent, masterclasses, joint webinars and extra.

Atalia holds a Bachelor of Science in industrial engineering and administration and two Masters—MBA and Enterprise Analytics.

Meet Atalia Horenshtien