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erwin Releases New Version of Industry-Defining Data Modeler to Support Digital Transformation, Cloud Migration and Infrastructure Modernization

erwin DM now features metadata-driven automation capabilities and support for data warehouse and DBMS modernization to ensure data governance and reduce data management costs and data-related risks

MELVILLE, N.Y., June 23, 2020 — erwin, Inc., the data governance company, today announced the availability of the latest version of the world’s No. 1 data modeling solution, erwin Data Modeler (erwin DM). The update features new metadata-driven automation capabilities and facilitates moving legacy, premise-based data sources to modern cloud platforms to ensure proper data governance.

erwin DM provides metadata and schema visualization, a well-governed and integrated process for defining/designing data assets of all types, and centralization and integration of business and semantic metadata – all to accelerate data governance and increase enterprise data literacy and collaboration. Automated schema design and migration helps organizations adopt modern DBMS platforms and data warehouse architectures. In fact, erwin recently announced its partnership with Snowflake.

“As a result of COVID 19, businesses around the world are drastically stepping up their digital transformation efforts, including moving their legacy data to the cloud to ensure it’s more available for decision-making,” says erwin CEO Adam Famularo. ”So we continue to invest in the technology we pioneered to ensure customers can understand, design and deploy new data sources, plus support data governance and intelligence efforts, to further reduce data management costs and data-related risks, while improving the quality and agility of an organization’s overall data capability.”

erwin DM’s specific new functionality includes:

  • erwin DM Connect for DI: Automatically harvests erwin data models and the associated metadata and then ingests it into the erwin Data Intelligence Suite (erwin DI). The model metadata feeds the erwin Data Catalog and the business information stored in the models populates the erwin DI Business Glossary Manager. Business metadata can then be associated with physical assets, business glossary development can be accelerated with model-driven naming standards, and models themselves can be socialized with a wider range of stakeholders.
  • Native support for Snowflake (4.1.x) and MariaDB (10.x) databases: erwin DM now fully supports these modern DBMS platforms, thus removing barriers, reducing costs and mitigating the risks associated with migrating legacy databases to these platforms. erwin’s model-driven schema transformation accelerates the successful adoption of Snowflake and MariaDB technologies, automating the engineering and deployment of schema from the models and auto-documents existing schema into reusable models. Watch a demo of erwin’s native support for Snowflake.
  • Centralized management and governance of naming standards: erwin DM Workgroup Edition users now can centrally create and manage reusable naming standards (NSM) across erwin data models and entire data architectures. Standardize how model objectives are named and auto-transform names between local and physical models for greater agility and consistency in model creation, granular versioning of naming standards maps, and increase efficiency and risk mitigation.

Other usability and design-task automation enhancements also have been made to help increase data modeler productivity.

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