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 |
|
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Alteryx: Analytics 11.5 (or higher) Snowflake: ODBC Driver — download from the ODBC Download page |
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Amazon SageMaker: No requirements Snowflake: No requirements |
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Big Squid: No requirements Snowflake: No requirements |
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BoostKPI: No requirements Snowflake: No requirements |
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Databricks: Runtime 4.2 Snowflake: No requirements |
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Dataiku: DSS Snowflake: JDBC Driver — download from the JDBC Driver page in the Maven Central Repository |
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DataRobot: No requirements Snowflake: No requirements |
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Domino: 3.6 (or higher) Snowflake: See the Domino documentation for requirements |
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H2O.ai: Driverless AI 1.4.2 (or higher) Snowflake: No requirements |
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Hex: No requirements Snowflake: No requirements |
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KNIME:
Snowflake: None (JDBC Driver embedded in the KNIME extension); other Snowflake drivers also supported |
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Qubole: Enterprise Edition Snowflake: No requirements |
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SAS:
Snowflake: ODBC Driver — download from the ODBC Download page |
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Spark: 3.0 (or higher) Scala: 2.12 or 2.13 Snowflake:
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Tellius: None Snowflake: None |
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Zepl: No requirements Snowflake:
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