Maximizing Existing Snowflake Investments
Some companies have spent vital cash on instruments to stay revolutionary and aggressive. While this may be a superb technique for a future-oriented firm, it may possibly show futile in the event you don’t maximize the worth of your funding. According to Flexera1, 92% of enterprises have a multi-cloud technique, whereas 80% have a hybrid cloud technique.
Integrating totally different programs, information sources, and applied sciences inside an ecosystem may be tough and time-consuming, resulting in inefficiencies, information silos, damaged machine studying fashions, and locked ROI.
The DataRobotic AI Platform and the Snowflake Data 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 Improvements
To assist clients maximize their Snowflake funding, DataRobotic is extending its Snowflake integration to assist clients rapidly iterate, enhance fashions, and full the ML lifecycle with out repeated configuration.
This consists of:
- Supporting Snowflake External OAuth configuration
- Leveraging Snowpark for exploratory information evaluation with DataRobotic-hosted Notebooks and mannequin scoring.
- A seamless consumer expertise when deploying and monitoring DataRobotic fashions to Snowflake
- Monitoring service well being, drift, and accuracy of DataRobotic fashions in Snowflake
“Organizations are looking for mature data science platforms that can scale to the size of their entire business. With the latest capabilities launched by DataRobot, customers can now guarantee the security and governance of their data used for ML, while simultaneously increasing the accessibility, performance, and efficiency of data preparation, model training, and model observability by their users,” mentioned Miles Adkins, Data Cloud Principal, AI/ML at Snowflake. “By bringing the unmatched AutoML capabilities of DataRobot to the data in Snowflake’s Data Cloud, customers get a seamless and comprehensive enterprise-grade data science platform.”
Complete the Machine Learning Lifecycle, Without Repeated Configuration
Connecting to Snowflake
Connect to Snowflake by way of exterior identification suppliers utilizing Snowflake External OAuth with out offering consumer and password credentials to DataRobotic. Reduce your safety perimeter by reusing your present Snowflake safety insurance policies with DataRobotic.
Learn extra about Snowflake External OAuth.
Exploratory Data Analysis
After we connect with Snowflake, we are able to begin our ML experiment.
We not too long ago introduced DataRobotic’s new Hosted Notebooks functionality.
For our joint resolution with Snowflake, because of this code-first customers can use DataRobotic’s hosted Notebooks because the interface and Snowpark processes the information instantly within the information 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 can take pleasure in a hosted expertise with code snippets, versioning, and easy setting administration for speedy AI experimentation.
Learn extra about DataRobotic hosted notebooks.
Model Training
Once the information is ready, customers select their most well-liked method for mannequin improvement utilizing DataRobotic AutoML by way of the GUI, hosted Notebooks, or each.
When the coaching course of is full, DataRobotic will advocate the best-performing mannequin for manufacturing based mostly on the chosen metric and supply a proof.
Model Deployment
Customers want the pliability to deploy fashions into totally different environments. Deploying to Snowflake reduces infrastructure operations complexity, information switch latency and related prices, whereas bettering effectivity and offering close to limitless scale.
A brand new Snowflake prediction setting configured by DataRobotic will robotically handle and management the setting, together with mannequin deployment and alternative.
When deploying a DataRobotic mannequin to Snowflake, this new seamless integration considerably improves the consumer expertise, reduces effort and time, and eliminates consumer errors.
The automated deployment pushes skilled fashions as Java UDFs, operating scalable inference inside Snowflake, and leveraging Snowpark to attain the information for pace and elasticity, whereas conserving information in place.
Model Monitoring
Internal and exterior components have an effect on fashions’ efficiency.
The new monitoring job functionality is run seamlessly from the DataRobotic GUI helps clients maintain monitor of their enterprise choices based mostly on predictions and precise information modifications 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, information drift, and accuracy over time and will help decide mannequin accountability.
Learn extra concerning the new monitoring job and automated deployment.
There’s extra coming
We have extra thrilling capabilities to share, many associated to the Snowflake integration, which might be introduced on the DataRobotic 9.0 launch occasion on March sixteenth. Register right here to be a part of this digital occasion.
If you might be already a buyer of Snowflake and DataRobotic, attain out to your account group to stand up to hurry on these new options.
Getting Started with DataRobotic AI and Snowflake, the Data Cloud
DataRobotic 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. Learn extra at DataRobot.com/Snowflake.
1 Source: Flexera 2021 State of the Cloud Report
About the creator
Global Technical Product Advocacy Lead, DataRobotic
Atalia Horenshtien is a Global Technical Product Advocacy Lead at DataRobotic. She performs an important position because the lead developer of the DataRobotic technical market story and works intently with product, advertising and marketing, and gross sales. As a former Customer Facing Data Scientist at DataRobotic, Atalia labored with clients in several industries as a trusted advisor on AI, solved advanced information science issues, and helped them unlock enterprise worth throughout the group.
Whether chatting with clients and companions or presenting at business occasions, she helps with advocating the DataRobotic story and the best way to undertake AI/ML throughout the group utilizing the DataRobotic platform. Some of her talking classes on totally different subjects like MLOps, Time Series Forecasting, Sports tasks, and use circumstances from varied verticals in business occasions like AI Summit NY, AI Summit Silicon Valley, Marketing AI Conference (MAICON), and companions occasions equivalent to Snowflake Summit, Google Next, masterclasses, joint webinars and extra.
Atalia holds a Bachelor of Science in industrial engineering and administration and two Masters—MBA and Business Analytics.