erwin Releases Enhanced Data Modeler
June 23, 2020
released 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:
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.