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 |
|
||
Amazon SageMaker: No requirements Snowflake: No requirements |
|
||
Big Squid: No requirements Snowflake: No requirements |
|
||
Databricks: Runtime 4.2 Snowflake: No requirements |
|
||
Dataiku: DSS Snowflake: JDBC Driver — download from Maven |
|
||
DataRobot: No requirements Snowflake: No requirements |
|
||
Domino: 3.6 (or higher) Snowflake: See the Domino documentation for requirements |
|
||
H2O.ai: Driverless AI 1.4.2 (or higher) Snowflake: No requirements |
|
||
Qubole: Enterprise Edition Snowflake: No requirements |
|
||
SAS:
Snowflake: ODBC Driver — download from the Snowflake Client Repository |
|
||
Spark: 3.0 (or higher) Scala: 2.12 or 2.13 Snowflake:
|
|
||
Zepl: No requirements Snowflake:
|
|