In an enterprise, it is quite common for someone using one or more warehouses to identify the need for an enterprise knowledge graph. However, these warehouses might lack the agility to keep up with the changing needs of the enterprise. Nevertheless, these warehouses can be used as a starting point for an ontology.
Data warehouses have captured something the enterprise has found to be a helpful commonality among several primitive data sources. Hence, they can be used as a shortcut to building an ontology. Depending on the foundational technology of the warehouse, its schema may be easy to query or maybe not. Regardless of how much effort is needed to get that schema, the effort is bound to be worth it because the first ontology can simply be an expression of this schema.
Furthermore, many semantic layer needs are met as it links to multiple data resources that contribute to the warehouse. In addition, the warehouse is a data asset that can be linked to a semantic layer with minimal effort. Thereby immediately providing value because the schema is a data asset in its own right and can be queried and developed further.
The next step is to use the agility of the ontology to add in new distinctions, connections, or data sources. For instance, it will have terms that the enterprise is already familiar with and will allow it to either extend or even change them. Besides, the ontology has a built-in connection to existing business practices. If anyone complains that the old warehouse is doing something wrong, that will help identify what needs to be developed next, which is the very definition of agility.
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