What’s new in erwin Data Modeler 14

Watch this 6-minute video to learn how erwin by Quest customers can leverage data models within erwin Data Modeler and data modeling integration with erwin Data Intelligence to create, curate and share datasets within the erwin Data Marketplace.

New visualization and collaboration capabilities plus integration with the Databricks Unity Catalog are just the start of the added capabilities in erwin Data Modeler 12.5. To learn more, visit www.erwin.com/erwin-data-modeler.

erwin by Quest has led the way in data modeling with sophisticated, industry-leading functionality. And our dedication to provide an unequaled solution is shown in our most recent release. In this 30-minute video, you'll learn about all the advantages and technical innovations.

erwin by Quest has always been at the forefront of helping enterprises realize new data modeling advantages. The latest release of erwin Data Modeler by Quest now includes both relational and NoSQL data modeling, as well as other enhancements for designing, documenting, and deploying new data sources. Watch the video to learn more about them and how erwin Data Modeler meets all enterprise data modeling needs.

This video discusses the newest release of erwin Data Modeler, which includes native support for Snowflake and MariaDB, integration with the erwin Data Intelligence Suite, centralized naming standards mapping, and JDBC support.

This video supplements the existing erwin Data Modeler online training courses. It explores the software’s latest release, with an emphasis on the new user interface as well as the new scheduler tool for managing reverse-engineering jobs. Several productivity and miscellaneous enhancements are also discussed.

erwin Data Modeler is an award-winning data modeling tool used to find, visualize, design, deploy and standardize high-quality enterprise data assets. Watch this short video to learn how erwin Data Modeler: • Helps you discover and document any data from anywhere for consistency, clarity and artifact reuse across large-scale data integration • Enables master data management, metadata management, Big Data, business intelligence and analytics initiatives • Supports data governance and intelligence efforts