Deep cataloging has three major characteristics:

1) Covering all types of technologies

A data fabric provides a holistic view of data across the IT landscape. In this design, a data catalog needs to cover all types of technologies.

It must include not only databases, data warehouses, and data lakes, but also cloud resources, programming languages, APIs, ETL tools, and BI reporting products.

Without this foundational capability, a data catalog is partial and passive.

2) Automatically applying quality and business policies/rules.

An enterprise data catalog should incorporate quality metrics and visualize quality scores at every step of the data supply chain.

When you have a thorough understanding of the quality behind the assets, you can reduce costs by eliminating duplicated or unused data. What is more, deep cataloging provides automatic mapping of assets to terms and associating business policies/rules.

By doing so, organizations can enhance proactive data governance and enable better decision making.

3) Enabling collaboration and meeting the needs of all types of users.

One of the key benefits and capabilities of deep cataloging is a platform for collaboration and a single model with multiple uses.

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.

The ultimate goal of deep cataloging is to activate the data catalog and enable self-service.