erwin Data Modeler 9.7 Released
Erwin is also expanding its data management platform by launching a new version of its industry-leading data modeling solution.
What’s New
Microsoft SQL Server Support
Erwin Data Modeler is now certified to work with Microsoft SQL Server Release 2016.
Microsoft SQL Azure Support
Erwin Data Modeler is now certified; therefore, as a result, it can work effectively with Microsoft SQL Azure.
Teradata Support
In addition, it is important to note that Erwin Data Modeler now offers support for new features and capabilities. These include multivalue compression, which is introduced in Teradata v15.10.
Progress OpenEdge 11.6 Support
erwin Data Modeler is now certified to work with Progress OpenEdge 11.6.
Hadoop Hive Support
Erwin Data Modeler is now certified, allowing it to work efficiently with Hadoop Hive through the ODBC driver.
IIS Support
Erwin Data Modeler and Mart Server now support the following versions of IIS to work in the Mart:
- IIS 7
- IIS 8
- IIS 10.
Validate Previous Version Metadata in Model
Erwin Data Modeler now offers the possibility to validate metadata from previous versions. This allows you to choose how you want to load models created in previous versions of the product. In addition, this option is available under Tools > Options > General tab and works as follows:
- If this optionis selected, then it disables demanding loading and uses full loading, thus validating all components.
- On the other hand, if it is not selected, then the demanding load is enabled.
Metadata Integration Bridges Updated
Erwin Data Modeler not only supports new metadata bridges, but also allows you to import a schema from a variety of BIG DATA sources, including: Apache Hadoop, on the one hand, includes Hive, HBase and HCatalog. On the other hand, Google BigQuery offers a powerful solution for data analysis. In addition, there is the Pivotal Greenplum database, which can be accessed via JDBC, as well as the PostgreSQL database. MongoDB also stands out as a robust option for non-relational data warehousing. Finally, Apache Cassandra and DataStax Enterprise (Cassandra) provide scalable and efficient solutions for managing large volumes of data.
Productivity Enhancements
The overall productivity of Erwin Data Modeler has consequently been significantly improved thanks to the following functionalities and workflows:
- Go to Filtering dialog: This function allows you to filter the components of your model by Object Type. For more information, see section Find Entities, Tables and Views.
- Show selected Subject Area when leaving the Subject Area Editor: This option switches the Subject Area view to the selected subject area. In this way, you can easily navigate between areas without confusion.
- Bulk deletion of UDPs: This feature allows you to select and delete several user-defined properties (UDPs) simultaneously. For more details, refer to the User Defined Properties section.