Modeling - discovery - 23.1

Spectrum Discovery Guide

Product type
Product family
Spectrum > Discovery
Product name
Spectrum Discovery
Spectrum Discovery Guide
Topic type
How Do I
First publish date

Producing data-driven insights requires that technical teams and business teams have a common understanding of the organization's data assets and how those assets will be used to support business decisions. Technical teams understand the design of databases while business teams understand the business objects (such as customer, store, or vendor) that are of interest. Spectrum Discovery helps bridge this gap by providing physical modeling and logical modeling tools that are visually rich and independent of each other, enabling you to create both a technical view of data assets and a business view of objects of interest, and to link the two through mapping.

Logical Model

A logical model defines the objects that your business is interested in and the attributes of those objects, as well as how objects are related to each other. For example, a logical model for a customer might contain attributes for name and date of birth. It might also have a relationship to a home address object, which contains attributes for address lines, city, and postal code. Once you have defined the attributes of the objects your business is interested in, you can map physical data sources to the logical model's attributes, thereby identifying the specific data asset that will be used to populate that attribute.

Physical Model

A physical model organizes your organization's data assets in a meaningful way. A physical model makes it possible to pull data from individual tables, columns, and views to create a single resource that you can then use to supply data to logical models or to perform profiling.

Context Graph Model

A Context Graph model represents entities and relationships. It is used to identify connections among people, groups, and organizations as well as patterns of connectedness, distance, centrality, influence status and importance. In Spectrum Discovery, you can create an entirely new Context Graph model, or you can use a Logical Model as a template for a Context Graph model. You can also edit or delete any existing Context Graph model.


The built-in suggestion capabilities of Spectrum Discovery make mapping of logical to physical models an intuitive, effortless job. During the mapping process, the system suggests all the discovered tables and columns that map with the selected logical entities. For the suggested assets the semantic and data type are also displayed giving you the much needed context.