Loading...
You are here:  Home  >  Education Resources For Use & Management of Data  >  Data Daily | Data News  >  Current Article

erwin Releases New Version of Industry-Leading Data Modeling Solution

By   /  January 25, 2017  /  No Comments

by Angela Guess

A recent press release reports, “erwin Inc., the data management experts, today announced the availability of a new version of erwin DM™, the company’s market-leading data modeling solution used by more than 50,000 professionals around the world. The new erwin DM solution effectively models and governs any data assets stored anywhere for more effective and powerful business decision making. ‘Enterprises need to leverage data as a strategic asset to drive growth and competitive advantage in today’s marketplace. But they face an increasingly complex challenge managing data in a variety of formats and in locations that have sprawled beyond their walls to the cloud,’ said Adam Famularo, CEO of erwin Inc. ‘Our new erwin DM solution helps enterprises integrate new data management technologies and deployment methods into existing technology architectures, increasing data fluency and enabling it to be used, trusted and understood across the business’.”

The release goes on, “Said Bill Matera, Director of Industry Data Models at Teradata and a participant in the erwin beta program, ‘We are pleased with the innovation that erwin is bringing to the data management market. This release continues to build on support for our Teradata platform and Industry Data Models. The combination of these technologies helps us deliver the best analytic solutions to our customers.’ Highlights of the new release of erwin DM include: Expanded Support for Cloud, NoSQLand Traditional Data Sources. NoSQL metadata harvesting from MongoDB, Cassandra, DataStax, CouchDB and MarkLogic, and round-trip engineering with AWS Redshift as well as Hadoop distributions and cloud-deployed servers, such as Apache Hadoop Hive Server, HBase and Web HCatalog. Automated metadata harvesting of cloud data lakes on big data clusters, including Amazon S3 and Apache Hadoop HDFS, or from file servers, which is critical for today’s self-service data needs.”

Read more at PRweb.

Photo credit: erwin

You might also like...

Thinking Inside the Box: How to Audit an AI

Read More →