To process Snowplow behavioral data in Databricks, follow these steps:

• Stream Snowplow's enriched event data into Databricks using a system like Apache Kafka or AWS Kinesis for real-time ingestion
• Once the data lands in Databricks, use Apache Spark for data transformations and feature engineering
• Store processed data in Delta Lake, which supports ACID transactions and allows for easy querying of large datasets
• Apply machine learning models using Databricks' built-in MLflow to gain insights from the behavioral data