Machine Learning & Data Science

Also referred to as advanced analytics, artificial intelligence (AI), and “Big Data”, machine learning and data science cover a broad category of vendors, tools, and technologies that provide advanced capabilities for statistical and predictive modeling.

These tools and technologies often share some overlapping features and functionality with BI tools; however, they focus less on analyzing/reporting past data. Instead, they focus on examining large data sets to discover patterns and uncover useful business information that can be used to predict future trends.

The following machine learning and data science platforms and technologies are known to provide native connectivity to Snowflake:

Solution

Version / Installation Requirements

Notes

Alteryx

Available in Partner Connect

Alteryx: Analytics 11.5 (or higher)

Snowflake: ODBC Driver — download from the Snowflake Client Repository

Amazon SageMaker

Amazon SageMaker: No requirements

Snowflake: No requirements

Big Squid

Big Squid: No requirements

Snowflake: No requirements

Databricks

Databricks: Runtime 4.2

Snowflake: No requirements

Dataiku

Available in Partner Connect

Dataiku: DSS

Snowflake: JDBC Driver — download from Maven

DataRobot

Available in Partner Connect

DataRobot: No requirements

Snowflake: No requirements

Domino

Domino: 3.6 (or higher)

Snowflake: See the Domino documentation for requirements

H2O.ai

Available in Partner Connect

H2O.ai: Driverless AI 1.4.2 (or higher)

Snowflake: No requirements

Qubole

Qubole: Enterprise Edition

Snowflake: No requirements

R Language dplyr

R Language: No requirements

dplyr: 0.4.3

Snowflake:

SAS

SAS:

  • Cloud Analytic Services 3.4 (or higher)

  • SAS/ACCESS 9.4 (or higher) for Relational Databases

Snowflake: ODBC Driver — download from the Snowflake Client Repository

Apache Spark

Spark: 2.3 (or higher)

Scala: 2.11 (or higher)

Snowflake:

Zepl

Available in Partner Connect

Zepl: No requirements

Snowflake: