Basic SQL Recipes for Web Data in Snowplow
Blog post from Snowplow
Mastering foundational SQL queries is crucial for extracting actionable insights from Snowplow data, which is rich in event-level information. Essential SQL recipes for web data analysis include counting page views by URL to assess user engagement, calculating average session duration to understand content interaction time, and identifying top referrers to track sources of traffic. Additionally, calculating conversion rates helps measure key actions like sign-ups or purchases, and tracking users across sessions allows for deeper behavioral analysis. These foundational queries enable data engineers and analysts to quickly extract insights and form the basis for developing more complex data models, with further advanced SQL recipes to be explored in future discussions.