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$800/monthly
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Snowplow supports compliant operations through its first-party data model with centralized schema enforcement and full ownership over storage and processing. It offers customizable enrichment pipelines, IP anonymization, consent management integration, and configurable data retention policies, all within your own cloud environment for full audit trails and data lineage.
Snowplow utilizes over 130 built-in enrichments, including user-agent parsing, sophisticated bot filtering, and device fingerprinting, to enhance data quality. Schema validation at the source prevents malformed data, while enrichment-level filtering removes noise, ensuring clean and well-structured datasets for analysis and AI applications.
The Data Product Studio allows teams to define and document tracking plans with granular detail, including ownership and semantic descriptions. It fosters collaboration by enabling teams to subscribe to, reuse, and receive alerts about tracking plans, accelerating the creation of new use cases while maintaining organizational standards.
Yes, Snowplow can leverage various data governance tools. For data lineage and cataloging, it can integrate with Apache Atlas, Amundsen, and OpenLineage, while for data quality and testing, it supports tools like Great Expectations and dbt's built-in capabilities.
The Self-Hosted Pipeline is a self-managed option for running a single Snowplow data pipeline in production, primarily for previous open-source users. The Snowplow Platform is a fully managed, scalable solution designed for production workloads, offering real-time data pipelines, a UI console, AI-ready modeling, and enterprise security.
Source: snowplow.io