Getting Started: Tutorial#

Scenario#

The marketing team at your company wants to find segments of customers with similar purchasing behavior so they can target them with more personalized marketing campaigns, and they’ve asked you to help. Fortunately, you’ve got the RAI Native App installed in your organization’s Snowflake account!

In this tutorial, you’ll use a portion of the sample TPC-DS dataset available in Snowflake to create a model of retail business sales. You’ll use graph analytics to detect customer segments with similar purchasing behavior, and then export the segment data to a Snowflake table for the marketing team to use.

Objectives#

After completing this tutorial, you’ll know how to:

• Create a model with entities derived from Snowflake tables.
• Create graphs and use graph algorithms.
• Visualize entities and relationships in the model.
• Export data from the model to a Snowflake table.
• Structure a project for reuse and extension.

Contents#

• Part One: Build a RAI Model

  • Set Up Your Environment
  • Configure Your Snowflake Connection
  • Get the Sample Data
  • Model the Data
  • Extend the Model
  • Detect Customer Segments with Graph Analytics
  • Explore the Differences Between Customer Segments
  • Export Segment Data to Snowflake
  • Summary and Next Steps

• Part Two: Build an App

  • Set Up the Project Environment
  • Create a raiconfig.toml File
  • Create a Model Module
  • Build a Streamlit App
  • Create a Model Package
  • Summary and Next Steps