Ontology
In the context of data analytics, ontology is the process of adding meaning to raw data by mapping it to real-world objects, concepts, and processes. It involves transforming data into a format that accurately reflects the scenarios and contexts your organization operates in.
Mapping your ontology includes organizing, categorizing, and relating data to create models that mirror your organization's business logic and reality. This process involves defining entities (like customers or products), their dimensions (such as age or department), and the relationships between them (for example, a customer can purchase multiple products). These models create an abstraction layer over raw data tables and columns, enabling users to interact with data more intuitively, focused, and relevantly.
Ontology page
The ontology page is divided into three parts:
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Entities - Displayed on the left side, this is a list of all the entities in your data model. You can search or select entities you want to edit or create a new one).
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Entity Table - Displayed in the middle section, this table provides visibility into the actual values of your data, where every column represents a dimension. By default, the primary keys and the "name" dimension are displayed, and you can add columns and filters to customize your view.
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Entity Mapping - Displayed on the right side, this is a list of all the entity's dimensions and relationships. You can tap into each object to make edits or create new ones.
For more information about managing your ontology, check out the Semantic Mapping documentation.