📄️ About semantic models
In this section, we provide an overview of semantic model; an essential piece of Sightfull; transforming raw data into meaningful information and creating a solid, consistent foundation for the metric layer. This introduction presents the what, why, how of semantic model and sets the stage for deeper exploration into its key components: entities, dimensions, and relationships.
📄️ Building your first entity
Welcome to this step-by-step guide for creating your first entity in Sightfull. This tutorial will walk you through the basics of creating entities. It focuses on their core components and integrating these components. Let's embark on this journey to build a foundational entity.
📄️ Entities
In Sightfull, entities play a critical role in the structure and interpretation of data. This document outlines the schema structure of an Entity YAML file, providing insights into how entities are defined and utilized within the semantic model.
📄️ Dimensions
Dimensions define the characteristics and features of the entities in your semantic models. They play a critical role in making your data more meaningful. In this document we will cover everything you need to know to use dimensions to build effective semantic models; what they are, why they're important, and how to use them effectively.
📄️ Relationships
Relationships determine how entities in your semantic models are associated, forming a web of interconnected data. This document explores the significance, types, and practical implementation of relationships in semantic mapping.
📄️ What is ontology?
Ontology is a set of concepts and categories in a domain that shows their properties and relations between them. In the realm of data analytics, it's a fundamental concept that significantly influences how data is understood and utilized within organizations. This page provides an overview of ontology in the context of Sightfull and its role in shaping a coherent and effective data strategy.
🗃️ Parameters
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