Hosted by Information Management

Data is the key to new business opportunities and new experiences for users. However, using data without in-depth knowledge can lead to poor decisions, missed opportunities, and negative outcomes.

But there is a better way: Machine learning techniques combined with cataloging, classification, and entity correlation create an automated data discovery model. This “discovery in depth” can run unsupervised processes that will create a complete catalog of all data, and tell you whose data it is, what it is, and what it is related to. This frees data professionals from tedious manual tagging and labeling, and allows them to focus on using the data to add value to the organization.

Watch this on-demand web seminar with Dan Sholler from BigID to learn:

  1. Why most catalogs do not include all data
  2. Steps to unsupervised discovery: Catalog, classify and correlate your data
  3. How to use discovery to drive governance and policy
  4. How to build an automated and repeatable data catalog
Dan Sholler
Sr. Director of Product Marketing
Jim Ericson
Consultant, Editor Emeritus
Information Management

Sponsor Content From:


Arizent takes your privacy seriously. We collect and use your data only for our own product research, client analytics and to inform you of products and services we think may be of interest to you.
By registering you agree with our Subscription Agreement and Privacy Policy.