MetaWizard supports metadata ingestion from more than 70 platforms, including relational databases, cloud warehouses, NoSQL systems, ETL tools, BI platforms, modeling standards, and file formats such as JSON, XML, CSV, and XMI. This allows teams to bring legacy structures, source systems, and distributed assets into a unified modeling environment.
Teams can export models and metadata directly into BI, ETL, governance, catalog, and analytics platforms. The exported metadata retains its structure, definitions, classifications, and relationships, ensuring downstream systems receive clean, governed, and standardized information without manual reconstruction.
The bridges integrate with databases, data lakes, lakehouses, and cloud storage systems such as Snowflake, BigQuery, Redshift, Hadoop, Hive, MongoDB, and more. This enables organizations to move metadata freely between on-prem and cloud platforms while maintaining consistency across environments.
After metadata is imported, ER/Studio applies naming conventions, glossary links, and governance rules to standardize structures and definitions across systems. This reduces inconsistencies from legacy environments, aligns technical fields with business terms, and provides cleaner metadata for platforms like Collibra and Microsoft Purview.
Instead of rebuilding models by hand, MetaWizard automates the capture and transformation of source metadata. This shortens onboarding time for new systems, eliminates copy-and-rebuild tasks, reduces human error, and ensures that imported structures reflect the actual production environment.
