Snowflake¶
The articles in this section progress from data ingest to creating projects and machine learning models based on historic training sets, and finally to scoring new data through deployed models via several deployment methodologies:
| Topic | Describes... |
|---|---|
| Data ingest | Retrieving data for Snowflake project creation. |
| Wrangle Snowflake data in DataRobot | Using Workbench in DataRobot, build wrangling recipes and push down those transformations to Snowflake where they are applied to the source data by leveraging Snowflake SQL. |
| Real-time predictions | Using the API to score Snowflake data. |
| Server-side model scoring | Using the API to integrate your deployment with Snowflake to feed data to your model for predictions and to write those predictions back to your Snowflake Database. |
| External functions and streams | Using external API call functions to create a Snowflake scoring pipeline. |
| Generate Snowflake UDF Scoring Code | Using the DataRobot Scoring Code JAR as a user-defined function (UDF) on Snowflake. |
Updated March 8, 2024
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