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Railinc: Best Practices for Deploying and Adopting an Intelligent Data Catalog

As Railinc modernizes its data infrastructure, critical data has become distributed across Oracle, data lake and tools like SAS, and business users have been challenged to find and understand the data they need. Railinc embarked on a major effort across business & IT to address this problem by cataloging all data assets and adding business context to the data to enable easy search and discovery. Confidence in the data was improved through visibility into how datasets were created and business descriptions and tags that added business context, along with a focused/phased approach to drive business user adoption. Railinc will share valuable lessons and best practices related to both: (1) deployment and scaling; (2) driving business user adoption.

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This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.