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: Analytics 11.5 (or higher) Snowflake: ODBC Driver — download from the Snowflake Client Repository	Available for trial via Snowflake Partner Connect. Validated by the Snowflake Ready Technology Validation Program. Additional resources: Snowflake In-Database Functionality Now Available (Alteryx Community Blog) Supported Data Sources — Snowflake (Alteryx Documentation)
		Amazon SageMaker: No requirements Snowflake: No requirements	Additional resources: Developer Guide > Prepare and Analyze Datasets > Import data from Snowflake (AWS Documentation) Preconfigured Amazon SageMaker Instance with Snowflake Connector (Snowflake Blog)
		Big Squid: No requirements Snowflake: No requirements	Validated by the Snowflake Ready Technology Validation Program. Additional resources: How Do I Create a Snowflake Connection? (Big Squid Support)
		Databricks: Runtime 4.2 Snowflake: No requirements	Integration implemented through the Snowflake Connector for Spark embedded in Databricks Runtime. Additional resources: Data Sources — Snowflake (Databricks Documentation)
		Dataiku: DSS Snowflake: JDBC Driver — download from Maven	Available for trial via Snowflake Partner Connect. Validated by the Snowflake Ready Technology Validation Program. Additional resources: Connecting to Data > SQL Databases > Snowflake (Dataiku Documentation)
		DataRobot: No requirements Snowflake: No requirements	Available for trial via Snowflake Partner Connect. Validated by the Snowflake Ready Technology Validation Program. Additional resources: The Power of DataRobot + Snowflake (DataRobot Blog)
		Domino: 3.6 (or higher) Snowflake: See the Domino documentation for requirements	Additional resources: Connecting to Snowflake from Domino (Domino Documentation)
		H2O.ai: Driverless AI 1.4.2 (or higher) Snowflake: No requirements	Available for trial via Snowflake Partner Connect. Validated by the Snowflake Ready Technology Validation Program. Additional resources: Using Data Connectors with Native Installs - Snowflake (H2O.ai Documentation)
		Qubole: Enterprise Edition Snowflake: No requirements	Integration implemented through the Snowflake Connector for Spark embedded in Qubole Data Service (QDS) Additional resources: Qubole Quickstart Guide (Qubole Documentation) Qubole-Snowflake Integration Guide (Qubole Documentation)
		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	Additional resources: Snowflake: Data Connector Specifics (SAS Documentation) SAS/ACCESS Interface to Snowflake (SAS Documentation)
		Spark: 3.0 (or higher) Scala: 2.12 or 2.13 Snowflake: JDBC Driver — download from Maven Connector for Spark — download from Maven	Additional resources: Configuring Snowflake to Communicate with Spark Running on EMR (Snowflake Community)
		Zepl: No requirements Snowflake: JDBC Driver — download from Maven Connector for Spark — download from Maven	Available for trial via Snowflake Partner Connect. Additional resources: Zepl and Snowflake Bring Data Science as a Service to Cloud Data Warehouses (Zepl Blog) Getting Started with Zepl and Snowflake in Minutes (Zepl Blog) Zepl and Snowflake — Data Science as a Service for your Cloud Warehouse (Zepl Solution Brief)