Common challenges with streaming data into Databricks include:

• Latency: Ensuring that the data is ingested, processed, and made available for analysis in real time
• Data volume: Managing large volumes of streaming data, which can overwhelm storage and processing systems
• Data quality: Ensuring that incoming Snowplow events are clean, valid, and reliable before processing
• Integration complexity: Integrating real-time data sources like Snowplow with Databricks and ensuring seamless data flow between systems