PUBLIC PREVIEW ANNOUNCEMENT
Snowpark
Use the language of your choice and familiar data frame constructs to build powerful and efficient pipelines and apps with the performance and ease of use of the Snowflake’s processing engine.
Snowflake for Data Science
Accelerate your workflow with near-unlimited access to data and data processing power.
Webinar
16 June: Virtual Hands-On Lab: Accelerate Machine Learning with Snowflake and Dataiku
Rapidly deliver the most predictive power to your machine learning models
Accelerate collecting and processing internal and third-party data with Snowflake’s Data Cloud. Realize the value of your models with a unified platform that enables cross-functional teams to build scalable data preparation, and model inference pipelines to transform data into actionable business insights.
PUBLIC PREVIEW ANNOUNCEMENT
ACCELERATE YOUR DATA SCIENCE WORKFLOW
One place to instantly access all relevant data
- Reduce the time to look for and request access to data, with a single point of access to a global network of trusted data
- Bring nearly all types of data into your model without complex pipelines. Rely on native support for structured, semi-structured (JSON, Avro, ORC, Parquet, or XML) and unstructured (in private preview) data
- Augment model performance with shared data sets from your business ecosystem, and third-party data providers via Snowflake Data Marketplace
Fast processing engine with minimal operational complexity
- Accelerate data preparation for any amount of data or users, with Snowflake’s multi-cluster compute architecture thanks to autoscaling and near-zero manual operations
- Transform data into features, using your language of choice with familiar dataframe constructs to build powerful and efficient pipelines with Snowpark.
- Quickly discover and address insights about feature quality, outliers, or other anomalies using built-in data profiling with table, plot, and histogram views.
Single platform to unify teams and tools around data
- Connect your ML tool of choice to Snowflake data, with native connectors and robust integrations from a broad ecosystem of partner tools
- Run scalable and secure ML inference with models running inside Snowflake as Java UDFs or communicating with a secure model endpoint with external functions
- Effortlessly make model results available in Snowflake for teams and applications to easily consume and act on ML-driven insights
“With Snowflake Data Cloud, we’ve removed data science bottlenecks so every analytics team across Pacific Life can maximize its potential.”
Kurpal Sandhu
Director of Data and Visualization, Pacific Life
“With Snowflake, we are much faster in developing and recalibrating models and algorithms, and we are able to leverage all of our data with state-of-the-art ML/AI tools to address business challenges and realize new opportunities.”
Volodymyr Sorokoumov
Senior Data Manager for Big Data and Advanced Analytics, Uniper
“We now have five data science teams across different business units that are doing analysis on top of Snowflake, but we’re not running into any constraints.”
Kiran Kanetkar
Sr. Director Data & Analytics, Petco
“Getting the best performance out of a risk model through data science is essential to our business. 1% improvement in the area under the curve of a model is equal to $1 million a year.”
Stephen Pidliskey
Senior Data Engineer, Beacon Street Services
Resources
Explore other workloads
Data Applications
Simplify developing data-intensive applications that scale cost-effectively and consistently deliver fast analytics.
Secure Data Sharing
Eliminate data silos and instantly and securely share governed data across your organization, and beyond
Data Lake
Improve data access, performance, and security with a modern data lake strategy.
Data Warehouse for Analytics
Enable everyone in your organization with fast access to a single source of data and eliminate the cost, complexity, and latency of your traditional data warehouse.
Ways to get started with Data Science on Snowflake
Accelerate your data science workflows with access to more data, faster feature engineering and direct integrations to leading ML tools.