Yes. Snowplow streams raw and enriched behavioral data into Databricks via structured, real-time pipelines, enabling Spark-based processing, ML model training, and advanced AI workloads.
The integration supports both streaming and batch processing modes, allowing teams to leverage Databricks' lakehouse architecture for cost-effective storage and compute.
Snowplow's governed, event-level data provides the high-quality foundation needed for feature engineering, model training, and AI application development within the Databricks environment.
The infrastructure’s dbt integration enables transformation workflows that prepare Snowplow data for Databricks AI/BI tools and machine learning pipelines.