How Snowplow collects events and entities and what makes this so powerful

Snowplow's unique approach to structuring events and entities significantly enhances data richness, quality, and flexibility, distinguishing it from other vendors. By defining custom data structures for events, which represent user actions, and entities, which provide context to these actions, Snowplow enables businesses to collect granular and tailored data aligned with their specific needs. Each event is automatically collected with 130 properties, allowing for detailed insights into user behavior, while entities can be appended to events to offer additional context. This setup, governed by self-describing schemas, ensures data accuracy and governance, as each piece of data is validated against these predefined schemas before being used. Moreover, Snowplow's data structures are not bound to specific platforms, making it easier to unify data from diverse sources like mobile, web, and third-party platforms into a common format, thus facilitating comprehensive data analysis. This flexibility allows companies to adapt their data collection as business needs evolve, offering a robust framework for deriving meaningful insights and optimizing data-driven strategies.