Data Quality Navigator - 2026 Pricing, Features, Reviews & Alternatives

Data Quality Navigator is an AI powered data quality management platform designed to provide comprehensive validation, cleansing, enrichment and governance capabilities for enterprise data. The system offers a systematic approach to improving data accuracy, compliance and efficiency across sourcing and procurement, logistics and production, data governance, ERP implementation and ESG initiatives. It serves medium and large enterprises across multiple industries, particularly those undergoing digital transformation or implementing new ERP systems or facing regulatory requirements that demand high quality data.

The platform features a suite of AI driven tools that work together to support comprehensive data quality management. Core components include AI for validation that detects data issues by comparing data against trusted sources and specialized data providers. Rule Mining AI identifies rules automatically and an extensive catalog of more than two thousand five hundred industry proven validation rules supports comprehensive checks. Designer AI facilitates the creation of custom validation rules by translating business expertise into executable logic. For data correction the platform provides structured cleansing workflows with clear assignment of responsibilities. Sweeper AI automates corrections by suggesting intelligent resolutions with minimal manual effort. Enrichment capabilities leverage external sources and specialized data providers to complete data automatically. Reader AI extracts relevant information from unstructured documents to deliver actionable insights. Monitoring dashboards highlight findings and track changes over time. The Workbench component supports collaborative error management with transparent workflows and detailed reporting.

Data Quality Navigator integrates with existing enterprise systems and supports diverse business applications. The platform connects with specialized data providers for both validation and enrichment processes. The system architecture supports integration with SAP S slash HANA and IFS deployments to maintain data quality before, during and after major system migrations. The platform provides application programming interfaces that enable deep embedding of data quality processes into business workflows and IT transformation projects. This integration ensures that data quality is embedded within operational processes rather than functioning as a separate capability.