Data Catalog

A data catalog is an organized inventory that shows where data scattered across various systems within a company is stored, what it's called, and what it means.

Think of how you find a book in a library. If there's a card catalog listing shelf numbers, titles, and authors, you can quickly find the book you want even in a huge library. Companies work the same way. If sales data, customer data, and on-site process data are stored under different names in different systems across departments, it takes forever just to find the information you need. A data catalog serves the role of organizing, in one place, which system each piece of data lives in, what it's called, and what it means.

Without a catalog, different departments may call the same data by different names, or people have to ask the person in charge every time they need something. With a catalog in place, the naming standard for data becomes unified, making it much easier and more accurate for both people and AI to find and use that data.

The article mentions building "a data catalog together with a standard management system to unify data standards across departments." It's important not to miss that a data catalog isn't the data itself, but rather an inventory that tells you where scattered data exists and what it is. Only once this inventory exists does subsequent work like linking relationships between data—such as with an ontology—become possible.

If you want to experience in a small way what a catalog does, try asking an AI chatbot something like this:

Organize the name, storage location, and purpose of the following files into a table: Sales_2025.xlsx, CustomerList_Final.csv, SitePhotos_January.zip

The process of gathering scattered items into a single organized table is exactly what a data catalog does at the scale of a large organization.