The Semantic Layer
In today's data-driven world, being data literate is a must for every business leader, but to enable this, technologists need to bridge the gap by delivering data in a language that mirrors the everyday words those leaders use to talk about their business.
According to Wikipedia, a Semantic Layer “maps complex data into familiar business terms such as product, customer, or revenue to offer a unified, consolidated view of data across the organization”.
The Semantic Web, on the other hand, provides a set of tools that can describe concepts, entities and their relationships, and then use those embedded semantics to reason over diverse data sources.
This is a match made in heaven! The Semantic Web has a set of technologies and standards that enable the creation of a Shared Semantic Layer. Here's how:
◽ your.schema.org: is an internal version of schema.org that can be used to define shared ontologies that map to downstream BI and AI tools, providing a business-friendly understanding of the data across the organisation. This is not a product but open-source code that you can download for free and adjust to your own needs.
◽ Linked Data: Linked data is a way of publishing data on the web and linking it to other data sources. By publishing internal data as virtual or materialised Linked Data Sets you can ensure that your data is linked to other data sources, providing a universal view. This is not a proprietary system, but an open standard free for anyone to use.
◽ Data Catalog: a Connected Data Catalog organises the Linked Datasets by the concepts in your.schema.org, providing a simple way to find data. You can use an off-the-shelf catalog or build a simple website yourself.
By employing these open technologies and standards, any organisation can construct a Shared Semantic Layer, which gives a uniform and consistent understanding of data. Most importantly, this makes technologists consciously think about designing data products in a way that directly delivers business value in business terms. I think this has the potential to revolutionise not only Data Engineering and MLOps but also empower all individuals to make informed decisions through data.
