One of the key benefits and capabilities of deep cataloging is a platform for collaboration and a single model with multiple use cases.
As part of an enterprise information intelligence graph, this data catalog facilitates communications between business and technical users. Powered by open APIs and integration with popular third-party platforms such as ServiceNow, this catalog bridges the gap between IT and business users.
No matter how complicated systems are, data flow is transparent for everybody to see in this data catalog. Enterprise segments/user personas see their view and how it relates to other views built upon the same model. Everybody can translate the information in his/her own and more meaningful way. For example, data stewards can set up policies and rules and exert control; and compliance officers can easily find the PII information and enforce rules and policies according to regulations. They can conduct all these activities independently, true instances of shadow IT.
A key difference between an active data catalog and a passive one is the ability to activate metadata. Embedded impact analysis is one of the features of an active data catalog or deep cataloging. This analysis shows the cause-and-effect, visualizing the consequences of any proposed changes. Cloud architect can use this analysis to make and execute data migration plans. Application developers can leverage it to do testing and prioritize resources.
As we can see that deep cataloging does not discriminate; all personas, business or technical, can benefit from it.
To sum up, deep cataloging, coupled with automation is an essential to building a data fabric. With broad technology coverage, automation, application of quality and other types of rules and policies, and versatility for all user personas, it enables enterprises to get the most value out of their data in a very short time.
About the author: Niu Bai, Ph.D. is the Head of Global Business Development and Partnerships at Orion Governance, Inc.