Qubole + Snowflake

Unlock additional value for Snowflake using Qubole to enable machine learning and data science capabilities

The Snowflake and Qubole integration enables companies to leverage machine learning (ML) and data science techniques to derive even greater value from critical information already present in Snowflake.

Companies interested in using ML with Snowflake often face limitations when training ML models with only a subset of data- this leads to inaccurate predictions. Data science teams may spend long hours training models and dealing with infrastructure restrictions that delay deployment of ML models. Qubole eliminates these limitations by automatically scaling and managing the Spark infrastructure on behalf of the data scientist. With this integration, our joint customers can leverage the complete Snowflake data set to train models while reducing the required training time by more than 50%. As a result, companies are able to maximize the value of their Snowflake data at a much faster pace.

Accelerate ROI for ML, data science and streaming processing use cases

  • Use Snowflake for fraud detection, customer churn analysis, data science exploration, etc.
  • Reduce the time to train ML algorithms

Reduce complexity and cost of running Spark.

  • Qubole automatically provisions, manages and scale Spark clusters
  • Leverage Snowflake Query Pushdown
  • Use Qubole for advanced (non-SQL) data preparation

Reduce manual configuration steps

  • Qubole Spark clusters are pre-configured to interact with Snowflake

Secured credential management between Qubole and Snowflake

Qubole Snowflake Integration Guide (AWS)
Boost Your Analytics with Machine Learning and Advanced Data Preparation
Qubole + Snowflake: Getting Started with Machine Learning
Qubole & Snowflake partnership briefing at Big Data World London, 2018
Qubole and Snowflake Bring Machine Learning to the Cloud Data Warehouse