Managing behavioral data quality before pushing it to Databricks involves several key steps:

• Data Validation: Use Snowplow's Enrich service to validate incoming event data, ensuring that it conforms to your defined schema
• Data Cleansing: Clean the data by removing outliers, correcting errors, and handling missing values
• Data Transformation: Use tools like dbt to transform raw Snowplow data into a structured format suitable for analysis
• Monitoring: Set up monitoring systems to ensure that data quality is maintained as new events are ingested