Quest enhances its Erwin data modeling and data intelligence platforms
Quest Software is announcing today enhancements to Erwin Data Modeler and Erwin Data Intelligence, the data operations and data management technologies it added to its portfolio with its acquisition of Erwin, Inc. in January of this year. Erwin Data Modeler is the modern-day instantiation of the ERwin/ERX data modeling product dating back to the early 1990s; Erwin Data Intelligence, meanwhile, combines IT-oriented data catalog and business user-/data steward-oriented data governance platforms.
Customers may have been worried how these platforms would fare under the Quest banner in terms of continued investment. With these new releases, Quest would seem to be demonstrating it views these assets as strategic to its entire data management portfolio and worthy of significant care and feeding.
Also read: Quest, Alteryx introduce new versions of core products
A model product
Capabilities in the new 2021 R1 release of Erwin Data Modeler include a mix of support for old-school and more recent data sources alike. There's native support for Couchbase, MongoDB and Cassandra on the NoSQL side; Data Vault 2.0 data modeling; support for JSON and AVRO file formats for the data lake crowd; and, in the land of relational databases – both on-premises and in the cloud – there's updated support and certifications for the latest versions of Oracle, Microsoft SQL Server, Microsoft Azure SQL Database and Microsoft Azure Synapse Analytics.
Beyond the native connectors and certifications, Erwin Data Modeler also provides JDBC connectivity for Oracle, Microsoft SQL Server, Microsoft Azure SQL Database, Snowflake, Couchbase, Cassandra and MongoDB. Quest says the release also adds a new object browser that displays all tables, views, indexes and relationships; API support and synchronization; and faster loading of large models.
Aye, aye, (data) steward
The Erwin Data Intelligence suite is comprised of two components, Erwin Data Catalog and Erwin Data Literacy, together aimed at helping organizations bridge the gap between the data governance needs of IT and those of business users.
The new version 11 release of the suite, expected in July, 2021 (i.e. next month), includes new capabilities aimed at increasing data visibility, expanding data governance efforts, and generally supporting more powerful analytics and automation. Within Erwin Data Catalog, new dashboards provide unified views of the data catalog, configurable by users. Users can assemble these dashboards from a library of attributes, including sensitive data distribution, top data sources, and data lineage. Erwin Data Literacy, meanwhile, adds a new dashboard as well, geared toward data stewards, allowing them to monitor top business data assets as well as top contributors and data governance action items.
Other enhanced capabilities include enhanced mind map (data lineage visualization) capabilities, a feature called enterprise tags, which will eventually be available from both the data catalog and data literacy sides of the suite; AI optimization of the catalog's data discovery tool to scan more physical and logical aspects of metadata, including business and technical naming descriptions, comments, definitions, and other attributes; as well as performance, search, and usability enhancements. The SQL Server version of Erwin Data Intelligence will provide the ability to define technical and business metadata in an organization's language of choice (i.e. natural/spoken language, not programming language).
Acquisitive legacy
In addition to its acquisition and subsequent spinoff by Dell, Quest has itself acquired nearly 40 companies in its 30+-year history. As such, it has built a data management and administration franchise that spans multiple technologies and multiple eras in the database industry. Modernizing and expanding the stack is important; so too is maintaining support for perennially popular paradigms and platforms (alliteration somewhat intentional), not to mention their customers.
It's a delicate balancing act to do both. By adding data modeling and data governance to the overall stack, as it did in January, then beefing up capabilities and database/data source support within those components, as it's doing now, Quest is helping companies master the numerous platforms within, and responsibilities around, their data estates. This is a hard job and requires a company with both significant history and the will to stay current. Further execution will be necessary for success but, with these announcements, it's clear Quest has its priorities straight.
Pamela Steger contributed to the reporting in this post