Automation Hub Data Model

Terms and Concepts

The structure of the Automation Hub Data Model is based on the following concepts:

Concept	Description
Explore	The starting point for exploration. The data is surfaced via Explores, which you can think of as a general entity that corresponds to the fields within it. For example, to build dashboards around the Automation Hub data, pick Automation Ideas or Idea Ageing Explores first and the fields containing the needed information and choose the proper visualization in order to display the results.
View	A view represents a table of data, whether that table is native to your database or was created using Looker’s derived table functionality. Within each view are field definitions, each of which typically corresponds to a column in the underlying table or a calculation in Looker.
Dimension	As part of a View within the Explore, the Dimension is a groupable field and can be used to filter query results. It can be one of the following: An attribute, which has a direct association to a column in an underlying table. A fact or numerical value. A derived value computed based on the values of other fields in a single row.
Measure	As part of a View within the Explore, the Measure parameter declares a new measure (aggregation) and specifies a name for that measure. Examples of measures types: `average`, `count`, `date`, `max`, `sum`.
Custom Fields	Custom Dimension Custom Measure Table calculation Start from scratch or use existing Dimensions and Measures to create new fields in the Data Model. Perform enhancements and data transformations by using formulas, filters, sorts.