Snowplow captures a wide range of timestamps across different stages of the data pipeline. Understanding how these timestamps are managed and how to handle timezone conversions is crucial for accurate data analysis. This post addresses common questions related to timezone handling in Snowplow.

Q: What timezones are used for Snowplow timestamps?

Snowplow stores its timestamps in UTC for consistency across the data pipeline. The specific timestamps and their timezones are as follows:

• collector_tstamp: UTC
  
  
• dvce_created_tstamp: UTC
  
  
• dvce_sent_tstamp: UTC
  
  
• etl_tstamp: UTC
  
  
• derived_tstamp: UTC or user-defined (based on true_tstamp)
  
  
• true_tstamp: User-defined
  
  

Q: How can I convert timestamps to a different timezone?

To convert Snowplow timestamps to a specific timezone, use the CONVERT_TIMEZONE function in Amazon Redshift. For example:

SELECT

  convert_timezone('UTC', 'America/New_York', derived_tstamp) AS local_time

FROM events;

For more dynamic conversion, you can leverage os_timezone or geo_timezone fields:

SELECT

  convert_timezone('UTC', COALESCE(os_timezone, geo_timezone, 'UTC'), derived_tstamp) AS user_local_time

FROM events;

Q: What are the potential pitfalls with timezone conversion?

• Missing Timezones: Some devices may not report an os_timezone, leading to potential fallback issues. Use COALESCE() to handle these cases.
  
  
• Database Timezone Database: Redshift’s timezone database may be outdated. Always verify compatibility, especially if your data includes recent timezone changes or adjustments.
  
  

Final Thoughts

Snowplow’s approach to timestamp management ensures data consistency by storing key timestamps in UTC. However, by leveraging CONVERT_TIMEZONE() and additional user-level timezone data, analysts can effectively localize events for more precise analysis and reporting. For more information on managing timezones in Snowplow, visit the official documentation.